EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as individual fingers from one hand. Several studies have reported spatial and temporal couplings of rhythmic activities at different frequency bands, suggesting the existence of well-defined spectral structures across multiple frequency bands. In the present study, spectral principal component analysis (PCA) was applied on EEG data, obtained from a finger movement task, to identify cross-frequency spectral structures. Features from identified spectral structures were examined in their spatial patterns, cross-condition pattern changes, detection capability of finger movements from resting, and decoding performance of individual finger movements in comparison to classic mu/beta rhythms. These new features reveal some similar, but more different spatial and spectral patterns as compared with classic mu/beta rhythms. Decoding results further indicate that these new features (91%) can detect finger movements much better than classic mu/beta rhythms (75.6%). More importantly, these new features reveal discriminative information about movements of different fingers (fine body-part movements), which is not available in classic mu/beta rhythms. The capability in decoding fingers (and hand gestures in the future) from EEG will contribute significantly to the development of non-invasive BCI and neuroprosthesis with intuitive and flexible controls. PMID:26388720

Optimizing Radiometric Processing and Feature Extraction of Drone Based Hyperspectral Frame Format Imagery for Estimation of Yield Quantity and Quality of a Grass Sward

NASA Astrophysics Data System (ADS)

Näsi, R.; Viljanen, N.; Oliveira, R.; Kaivosoja, J.; Niemeläinen, O.; Hakala, T.; Markelin, L.; Nezami, S.; Suomalainen, J.; Honkavaara, E.

2018-04-01

Light-weight 2D format hyperspectral imagers operable from unmanned aerial vehicles (UAV) have become common in various remote sensing tasks in recent years. Using these technologies, the area of interest is covered by multiple overlapping hypercubes, in other words multiview hyperspectral photogrammetric imagery, and each object point appears in many, even tens of individual hypercubes. The common practice is to calculate hyperspectral orthomosaics utilizing only the most nadir areas of the images. However, the redundancy of the data gives potential for much more versatile and thorough feature extraction. We investigated various options of extracting spectral features in the grass sward quantity evaluation task. In addition to the various sets of spectral features, we used photogrammetry-based ultra-high density point clouds to extract features describing the canopy 3D structure. Machine learning technique based on the Random Forest algorithm was used to estimate the fresh biomass. Results showed high accuracies for all investigated features sets. The estimation results using multiview data provided approximately 10 % better results than the most nadir orthophotos. The utilization of the photogrammetric 3D features improved estimation accuracy by approximately 40 % compared to approaches where only spectral features were applied. The best estimation RMSE of 239 kg/ha (6.0 %) was obtained with multiview anisotropy corrected data set and the 3D features.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum

NASA Astrophysics Data System (ADS)

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum.

PubMed

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Search for Feo and Pyroxene on MERCURY?S Surface

NASA Astrophysics Data System (ADS)

Sprague, Ann L.; Emery, Joshua P.

Results from spectral observations of Mercury's surface in the wavelength range 0.8 to 5.5 micrometers will be reported. The data were obtained at the NASA Infrared Telescope Facility on Mauna Kea Hawaii. We used SpeX a long slit imaging system developed at the IRTF for high resolving power spatially resolved spectroscopy throughout the solar system. We aligned the spectral slit with Mercury's geographic longitude and systematically moved it across the Earth-facing disk to obtain multiple disk-resolved spectral images. The entire data set provides spatial coverage of the Earth-facing disk limited only by atmospheric turbulence and the diffraction limit for each wavelength. We used SpeX in two spectral regions in the R 2000 mode. In the first case between 0.8 and 2.5 micrometer to search for the 0.9 to 1.0 micrometer reflectance absorption feature caused by the Fe2+ electronic transfer in FeO. We also measured the 4.5 to 5.5 micrometer flux from Mercury. This is a region of diagnostic features caused by the presence of volume scattering in pyroxene and olivine. These data will be compared to previous observations that showed an anomalous emission feature at 5.5 micrometer and to others that exhibited a feature closely resembling that from pyroxene.

Spectra of late type dwarf stars of known abundance for stellar population models

NASA Technical Reports Server (NTRS)

Oconnell, R. W.

1990-01-01

The project consisted of two parts. The first was to obtain new low-dispersion, long-wavelength, high S/N IUE spectra of F-G-K dwarf stars with previously determined abundances, temperatures, and gravities. To insure high quality, the spectra are either trailed, or multiple exposures are taken within the large aperture. Second, the spectra are assembled into a library which combines the new data with existing IUE Archive data to yield mean spectral energy distributions for each important type of star. My principal responsibility is the construction and maintenance of this UV spectral library. It covers the spectral range 1200-3200A and is maintained in two parts: a version including complete wavelength coverage at the full spectral resolution of the Low Resolution cameras; and a selected bandpass version, consisting of the mean flux in pre-selected 20A bands. These bands are centered on spectral features or continuum regions of special utility - e.g. the C IV lambda 1550 or Mg II lambda 2800 feature. In the middle-UV region, special emphasis is given to those features (including continuum 'breaks') which are most useful in the study of F-G-K star spectra in the integrated light of old stellar populations.

Behavioral state classification in epileptic brain using intracranial electrophysiology

NASA Astrophysics Data System (ADS)

Kremen, Vaclav; Duque, Juliano J.; Brinkmann, Benjamin H.; Berry, Brent M.; Kucewicz, Michal T.; Khadjevand, Fatemeh; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Worrell, Gregory A.

2017-04-01

Objective. Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach. Data from seven patients (age 34+/- 12 , 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1-600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results. Classification accuracy of 97.8  ±  0.3% (normal tissue) and 89.4  ±  0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8  ±  0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1  ±  1.6%). Spectral power in high frequency band features (Ripple (80-250 Hz), Fast Ripple (250-600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy  ⩾90% using a single electrode contact and single spectral feature. Significance. Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.

Spectral reflectance properties of major objects in desert oasis: a case study of the Weigan-Kuqa river delta oasis in Xinjiang, China.

PubMed

Zhang, Fei; Tiyip, Tashpolat; Ding, Jianli; Sawut, Mamat; Tashpolat, Nigara; Kung, Hsiangte; Han, Guihong; Gui, Dongwei

2012-08-01

Aiming at the remote sensing application has been increasingly relying on ground object spectral characteristics. In order to further research the spectral reflectance characteristics in arid area, this study was performed in the typical delta oasis of Weigan and Kuqa rivers located north of Tarim Basin. Data were collected from geo-targets at multiple sites in various field conditions. The spectra data were collected for different soil types including saline-alkaline soil, silt sandy soil, cotton field, and others; vegetations of Alhagi sparsifolia, Phragmites australis, Tamarix, Halostachys caspica, etc., and water bodies. Next, the data were processed to remove high-frequency noise, and the spectral curves were smoothed with the moving average method. The derivative spectrum was generated after eliminating environmental background noise so that to distinguish the original overlap spectra. After continuum removal of the undesirable absorbance, the spectrum curves were able to highlight features for both optical absorbance and reflectance. The spectrum information of each ground object is essential for fully utilizing the multispectrum data generated by remote sensing, which will need a representative spectral library. In this study using ENVI 4.5 software, a preliminary spectral library of surface features was constructed using the data surveyed in the study area. This library can support remote sensing activities such as feature investigation, vegetation classification, and environmental monitoring in the delta oasis region. Future plan will focus on sharing and standardizing the criteria of professional spectral library and to expand and promote the utilization of the spectral databases.

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

NASA Astrophysics Data System (ADS)

Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

2018-01-01

Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

Element-specific spectral imaging of multiple contrast agents: a phantom study

NASA Astrophysics Data System (ADS)

Panta, R. K.; Bell, S. T.; Healy, J. L.; Aamir, R.; Bateman, C. J.; Moghiseh, M.; Butler, A. P. H.; Anderson, N. G.

2018-02-01

This work demonstrates the feasibility of simultaneous discrimination of multiple contrast agents based on their element-specific and energy-dependent X-ray attenuation properties using a pre-clinical photon-counting spectral CT. We used a photon-counting based pre-clinical spectral CT scanner with four energy thresholds to measure the X-ray attenuation properties of various concentrations of iodine (9, 18 and 36 mg/ml), gadolinium (2, 4 and 8 mg/ml) and gold (2, 4 and 8 mg/ml) based contrast agents, calcium chloride (140 and 280 mg/ml) and water. We evaluated the spectral imaging performances of different energy threshold schemes between 25 to 82 keV at 118 kVp, based on K-factor and signal-to-noise ratio and ranked them. K-factor was defined as the X-ray attenuation in the K-edge containing energy range divided by the X-ray attenuation in the preceding energy range, expressed as a percentage. We evaluated the effectiveness of the optimised energy selection to discriminate all three contrast agents in a phantom of 33 mm diameter. A photon-counting spectral CT using four energy thresholds of 27, 33, 49 and 81 keV at 118 kVp simultaneously discriminated three contrast agents based on iodine, gadolinium and gold at various concentrations using their K-edge and energy-dependent X-ray attenuation features in a single scan. A ranking method to evaluate spectral imaging performance enabled energy thresholds to be optimised to discriminate iodine, gadolinium and gold contrast agents in a single spectral CT scan. Simultaneous discrimination of multiple contrast agents in a single scan is likely to open up new possibilities of improving the accuracy of disease diagnosis by simultaneously imaging multiple bio-markers each labelled with a nano-contrast agent.

Carriers of the astronomical 2175 ? extinction feature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J; Dai, Z; Ernie, R

2004-07-20

The 2175 {angstrom} extinction feature is by far the strongest spectral signature of interstellar dust observed by astronomers. Forty years after its discovery the origin of the feature and the nature of the carrier remain controversial. The feature is enigmatic because although its central wavelength is almost invariant its bandwidth varies strongly from one sightline to another, suggesting multiple carriers or a single carrier with variable properties. Using a monochromated transmission electron microscope and valence electron energy-loss spectroscopy we have detected a 5.7 eV (2175 {angstrom}) feature in submicrometer-sized interstellar grains within interplanetary dust particles (IDPs) collected in the stratosphere.more » The carriers are organic carbon and amorphous silicates that are abundant and closely associated with one another both in IDPs and in the interstellar medium. Multiple carriers rather than a single carrier may explain the invariant central wavelength and variable bandwidth of the astronomical 2175 {angstrom} feature.« less

Hierarchical image feature extraction by an irregular pyramid of polygonal partitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skurikhin, Alexei N

2008-01-01

We present an algorithmic framework for hierarchical image segmentation and feature extraction. We build a successive fine-to-coarse hierarchy of irregular polygonal partitions of the original image. This multiscale hierarchy forms the basis for object-oriented image analysis. The framework incorporates the Gestalt principles of visual perception, such as proximity and closure, and exploits spectral and textural similarities of polygonal partitions, while iteratively grouping them until dissimilarity criteria are exceeded. Seed polygons are built upon a triangular mesh composed of irregular sized triangles, whose spatial arrangement is adapted to the image content. This is achieved by building the triangular mesh on themore » top of detected spectral discontinuities (such as edges), which form a network of constraints for the Delaunay triangulation. The image is then represented as a spatial network in the form of a graph with vertices corresponding to the polygonal partitions and edges reflecting their relations. The iterative agglomeration of partitions into object-oriented segments is formulated as Minimum Spanning Tree (MST) construction. An important characteristic of the approach is that the agglomeration of polygonal partitions is constrained by the detected edges; thus the shapes of agglomerated partitions are more likely to correspond to the outlines of real-world objects. The constructed partitions and their spatial relations are characterized using spectral, textural and structural features based on proximity graphs. The framework allows searching for object-oriented features of interest across multiple levels of details of the built hierarchy and can be generalized to the multi-criteria MST to account for multiple criteria important for an application.« less

A fully-coupled discontinuous Galerkin spectral element method for two-phase flow in petroleum reservoirs

NASA Astrophysics Data System (ADS)

Taneja, Ankur; Higdon, Jonathan

2018-01-01

A high-order spectral element discontinuous Galerkin method is presented for simulating immiscible two-phase flow in petroleum reservoirs. The governing equations involve a coupled system of strongly nonlinear partial differential equations for the pressure and fluid saturation in the reservoir. A fully implicit method is used with a high-order accurate time integration using an implicit Rosenbrock method. Numerical tests give the first demonstration of high order hp spatial convergence results for multiphase flow in petroleum reservoirs with industry standard relative permeability models. High order convergence is shown formally for spectral elements with up to 8th order polynomials for both homogeneous and heterogeneous permeability fields. Numerical results are presented for multiphase fluid flow in heterogeneous reservoirs with complex geometric or geologic features using up to 11th order polynomials. Robust, stable simulations are presented for heterogeneous geologic features, including globally heterogeneous permeability fields, anisotropic permeability tensors, broad regions of low-permeability, high-permeability channels, thin shale barriers and thin high-permeability fractures. A major result of this paper is the demonstration that the resolution of the high order spectral element method may be exploited to achieve accurate results utilizing a simple cartesian mesh for non-conforming geological features. Eliminating the need to mesh to the boundaries of geological features greatly simplifies the workflow for petroleum engineers testing multiple scenarios in the face of uncertainty in the subsurface geology.

Wide-bandwidth high-resolution search for extraterrestrial intelligence

NASA Technical Reports Server (NTRS)

Horowitz, Paul

1995-01-01

Research was accomplished during the third year of the grant on: BETA architecture, an FFT array, a feature extractor, the Pentium array and workstation, and a radio astronomy spectrometer. The BETA (this SETI project) system architecture has been evolving generally in the direction of greater robustness against terrestrial interference. The new design adds a powerful state-memory feature, multiple simultaneous thresholds, and the ability to integrate multiple spectra in a flexible state-machine architecture. The FFT array is reported with regards to its hardware verification, array production, and control. The feature extractor is responsible for maintaining a moving baseline, recognizing large spectral peaks, following the progress of previously identified interesting spectral regions, and blocking signals from regions previously identified as containing interference. The Pentium array consists of 21 Pentium-based PC motherboards, each with 16 MByte of RAM and an Ethernet interface. Each motherboard receives and processes the data from a feature extractor/correlator board set, passing on the results of a first analysis to the central Unix workstation (through which each is also booted). The radio astronomy spectrometer is a technological spinoff from SETI work. It is proposed to be a combined spectrometer and power-accumulator, for use at Arecibo Observatory to search for neutral hydrogen emission from condensations of neutral hydrogen at high redshift (z = 5).

Estimating Achievable Accuracy for Global Imaging Spectroscopy Measurement of Non-Photosynthetic Vegetation Cover

NASA Astrophysics Data System (ADS)

Dennison, P. E.; Kokaly, R. F.; Daughtry, C. S. T.; Roberts, D. A.; Thompson, D. R.; Chambers, J. Q.; Nagler, P. L.; Okin, G. S.; Scarth, P.

2016-12-01

Terrestrial vegetation is dynamic, expressing seasonal, annual, and long-term changes in response to climate and disturbance. Phenology and disturbance (e.g. drought, insect attack, and wildfire) can result in a transition from photosynthesizing "green" vegetation to non-photosynthetic vegetation (NPV). NPV cover can include dead and senescent vegetation, plant litter, agricultural residues, and non-photosynthesizing stem tissue. NPV cover is poorly captured by conventional remote sensing vegetation indices, but it is readily separable from substrate cover based on spectral absorption features in the shortwave infrared. We will present past research motivating the need for global NPV measurements, establishing that mapping seasonal NPV cover is critical for improving our understanding of ecosystem function and carbon dynamics. We will also present new research that helps determine a best achievable accuracy for NPV cover estimation. To test the sensitivity of different NPV cover estimation methods, we simulated satellite imaging spectrometer data using field spectra collected over mixtures of NPV, green vegetation, and soil substrate. We incorporated atmospheric transmittance and modeled sensor noise to create simulated spectra with spectral resolutions ranging from 10 to 30 nm. We applied multiple methods of NPV estimation to the simulated spectra, including spectral indices, spectral feature analysis, multiple endmember spectral mixture analysis, and partial least squares regression, and compared the accuracy and bias of each method. These results prescribe sensor characteristics for an imaging spectrometer mission with NPV measurement capabilities, as well as a "Quantified Earth Science Objective" for global measurement of NPV cover. Copyright 2016, all rights reserved.

Feature extraction from multiple data sources using genetic programming

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Brumby, Steven P.; Pope, Paul A.; Eads, Damian R.; Esch-Mosher, Diana M.; Galassi, Mark C.; Harvey, Neal R.; McCulloch, Hersey D.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Bloch, Jeffrey J.; David, Nancy A.

2002-08-01

Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

[Spectral features analysis of Pinus massoniana with pest of Dendrolimus punctatus Walker and levels detection].

PubMed

Xu, Zhang-Hua; Liu, Jian; Yu, Kun-Yong; Gong, Cong-Hong; Xie, Wan-Jun; Tang, Meng-Ya; Lai, Ri-Wen; Li, Zeng-Lu

2013-02-01

Taking 51 field measured hyperspectral data with different pest levels in Yanping, Fujian Province as objects, the spectral reflectance and first derivative features of 4 levels of healthy, mild, moderate and severe insect pest were analyzed. On the basis of 7 detecting parameters construction, the pest level detecting models were built. The results showed that (1) the spectral reflectance of Pinus massoniana with pests were significantly lower than that of healthy state, and the higher the pest level, the lower the reflectance; (2) with the increase in pest level, the spectral reflectance curves' "green peak" and "red valley" of Pinus massoniana gradually disappeared, and the red edge was leveleds (3) the pest led to spectral "green peak" red shift, red edge position blue shift, but the changes in "red valley" and near-infrared position were complicated; (4) CARI, RES, REA and REDVI were highly relevant to pest levels, and the correlations between REP, RERVI, RENDVI and pest level were weak; (5) the multiple linear regression model with the variables of the 7 detection parameters could effectively detect the pest levels of Dendrolimus punctatus Walker, with both the estimation rate and accuracy above 0.85.

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Investigation of the variance and spectral anisotropies of the solar wind turbulence with multiple point spacecraft observations

NASA Astrophysics Data System (ADS)

Vech, Daniel; Chen, Christopher

2016-04-01

One of the most important features of the plasma turbulence is the anisotropy, which arises due to the presence of the magnetic field. The understanding of the anisotropy is particularly important to reveal how the turbulent cascade operates. It is well known that anisotropy exists with respect to the mean magnetic field, however recent theoretical studies suggested anisotropy with respect to the radial direction. The purpose of this study is to investigate the variance and spectral anisotropies of the solar wind turbulence with multiple point spacecraft observations. The study includes the Advanced Composition Analyzer (ACE), WIND and Cluster spacecraft data. The second order structure functions are derived for two different spacecraft configurations: when the pair of spacecraft are separated radially (with respect to the spacecraft -Sun line) and when they are separated along the transverse direction. We analyze the effect of the different sampling directions on the variance anisotropy, global spectral anisotropy, local 3D spectral anisotropy and discuss the implications for our understanding of solar wind turbulence.

The Hierarchical Cortical Organization of Human Speech Processing

PubMed Central

de Heer, Wendy A.; Huth, Alexander G.; Griffiths, Thomas L.

2017-01-01

Speech comprehension requires that the brain extract semantic meaning from the spectral features represented at the cochlea. To investigate this process, we performed an fMRI experiment in which five men and two women passively listened to several hours of natural narrative speech. We then used voxelwise modeling to predict BOLD responses based on three different feature spaces that represent the spectral, articulatory, and semantic properties of speech. The amount of variance explained by each feature space was then assessed using a separate validation dataset. Because some responses might be explained equally well by more than one feature space, we used a variance partitioning analysis to determine the fraction of the variance that was uniquely explained by each feature space. Consistent with previous studies, we found that speech comprehension involves hierarchical representations starting in primary auditory areas and moving laterally on the temporal lobe: spectral features are found in the core of A1, mixtures of spectral and articulatory in STG, mixtures of articulatory and semantic in STS, and semantic in STS and beyond. Our data also show that both hemispheres are equally and actively involved in speech perception and interpretation. Further, responses as early in the auditory hierarchy as in STS are more correlated with semantic than spectral representations. These results illustrate the importance of using natural speech in neurolinguistic research. Our methodology also provides an efficient way to simultaneously test multiple specific hypotheses about the representations of speech without using block designs and segmented or synthetic speech. SIGNIFICANCE STATEMENT To investigate the processing steps performed by the human brain to transform natural speech sound into meaningful language, we used models based on a hierarchical set of speech features to predict BOLD responses of individual voxels recorded in an fMRI experiment while subjects listened to natural speech. Both cerebral hemispheres were actively involved in speech processing in large and equal amounts. Also, the transformation from spectral features to semantic elements occurs early in the cortical speech-processing stream. Our experimental and analytical approaches are important alternatives and complements to standard approaches that use segmented speech and block designs, which report more laterality in speech processing and associated semantic processing to higher levels of cortex than reported here. PMID:28588065

Spectral imaging: principles and applications.

PubMed

Garini, Yuval; Young, Ian T; McNamara, George

2006-08-01

Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well. The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the algorithms are discussed with emphasis on the usage for different experimental modes (fluorescence and bright field). Finally, spectral imaging, like any method, should be evaluated in light of its advantages to specific applications, a selection of which is described. Spectral imaging is a relatively new technique and its full potential is yet to be exploited. Nevertheless, several applications have already shown its potential. (c) 2006 International Society for Analytical Cytology.

Land mine detection using multispectral image fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-03-29

Our system fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a varietymore » of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts. We use a supervised learning pattern recognition approach to detecting the metal and plastic land mines. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the spectral bands add value to the detection system. The most important features from the various sensors are fused using a supervised learning pattern classifier (the probabilistic neural network). We present results of experiments to detect land mines from real data collected from an airborne platform, and evaluate the usefulness of fusing feature information from multiple spectral bands.« less

Intelligent multi-spectral IR image segmentation

NASA Astrophysics Data System (ADS)

Lu, Thomas; Luong, Andrew; Heim, Stephen; Patel, Maharshi; Chen, Kang; Chao, Tien-Hsin; Chow, Edward; Torres, Gilbert

2017-05-01

This article presents a neural network based multi-spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. This article compares the neural network based segmentation method to the Wavelet-threshold and Grab-Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-spectral IR images.

Berkeley SuperNova Ia Program (BSNIP): Initial Spectral Analysis

NASA Astrophysics Data System (ADS)

Silverman, Jeffrey; Kong, J.; Ganeshalingam, M.; Li, W.; Filippenko, A. V.

2011-01-01

The Berkeley SuperNova Ia Program (BSNIP) has been observing nearby (z < 0.1) Type Ia supernovae (SNe Ia) both photometrically and spectroscopically for over two decades. Using telescopes at both Lick and Keck Observatories, we have amassed an extensive collection of well-sampled optical light curves with complementary spectra covering, on average, 3400-10,000 Å. In total, we have obtained nearly 600 spectra of over 200 SNe Ia with densely sampled multi-color light curves. The initial analysis of this dataset consists of accurately and robustly measuring the strength and position of various spectral features near maximum brightness. We determine the endpoints, pseudo-continuum, expansion velocity, equivalent width, and depth of each major feature observed in our wavelength range. For objects with multiple spectra near maximum brightness we investigate how these values change with time. From these measurements we also calculate velocity gradients and various flux ratios within a given spectrum which will allow us to explore correlations between spectral and photometric observables. Some possible correlations have been studied previously, but our dataset is unique in how self-consistent the data reduction and spectral feature measurements have been, and it is a factor of a few larger than most earlier studies. We will briefly summarize the contents of the full dataset as an introduction to our initial analysis. Some of our measurements of SN Ia spectral features, along with a few initial results from those measurements, will be presented. Finally, we will comment on our current progress and planned future work. We gratefully acknowledge the financial support of NSF grant AST-0908886, the TABASGO Foundation, and the Marc J. Staley Graduate Fellowship in Astronomy.

Thin cirrus clouds - Seasonal distribution over oceans deduced from Nimbus-4 IRIS

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Fraser, R. S.; Dalu, G.; Wu, Man-Li C.; Curran, R. J.

1988-01-01

Spectral differences in the extinction of the 10.8- and 12.6-micron bands of the IR window region, due to optically thin clouds, were found in the measurements made by both an airborne broadband IR radiometer and the IR interferometer spectrometer (IRIS) aboard the Nimbus-4 satellite; the extinction at 12.6 microns was significantly larger than that at 10.8 microns; both water and ice particles in the clouds can account for such spectral difference in extinction. Multiple scattering radiative transfer calculations of IRIS data revealed this spectral feature about 100 to 20 km away from the high-altitude cold clouds; it is assumed that this feature is related to the spreading of cirrus clouds. Based on this assumption, mean seasonal maps of the distribution of thin cirrus clouds over the oceans were deduced from the IRIS data. The maps show that such clouds are often present over the convectively active areas, such as ITCZ, SPCZ, and the Bay of Bengal during the summer monsoon.

Audio-Visual Speaker Diarization Based on Spatiotemporal Bayesian Fusion.

PubMed

Gebru, Israel D; Ba, Sileye; Li, Xiaofei; Horaud, Radu

2018-05-01

Speaker diarization consists of assigning speech signals to people engaged in a dialogue. An audio-visual spatiotemporal diarization model is proposed. The model is well suited for challenging scenarios that consist of several participants engaged in multi-party interaction while they move around and turn their heads towards the other participants rather than facing the cameras and the microphones. Multiple-person visual tracking is combined with multiple speech-source localization in order to tackle the speech-to-person association problem. The latter is solved within a novel audio-visual fusion method on the following grounds: binaural spectral features are first extracted from a microphone pair, then a supervised audio-visual alignment technique maps these features onto an image, and finally a semi-supervised clustering method assigns binaural spectral features to visible persons. The main advantage of this method over previous work is that it processes in a principled way speech signals uttered simultaneously by multiple persons. The diarization itself is cast into a latent-variable temporal graphical model that infers speaker identities and speech turns, based on the output of an audio-visual association process, executed at each time slice, and on the dynamics of the diarization variable itself. The proposed formulation yields an efficient exact inference procedure. A novel dataset, that contains audio-visual training data as well as a number of scenarios involving several participants engaged in formal and informal dialogue, is introduced. The proposed method is thoroughly tested and benchmarked with respect to several state-of-the art diarization algorithms.

An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images

NASA Astrophysics Data System (ADS)

Bhardwaj, Kaushal; Patra, Swarnajyoti

2018-04-01

Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.

Composition of whole and water extractable organic matter of cattle manure affected by management practices

USDA-ARS?s Scientific Manuscript database

Organic matter (OM) is a major component of animal manure. In this chapter, we present two case studies on the multiple spectral features of whole and water extractable organic matter (WEOM) of cattle (beef and dairy) manure affected by differing management practices. Using wet chemistry and Fourie...

Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor

NASA Astrophysics Data System (ADS)

Uzkent, Burak; Hoffman, Matthew J.; Vodacek, Anthony

2015-03-01

Object tracking in urban environments is an important and challenging problem that is traditionally tackled using visible and near infrared wavelengths. By inserting extended data such as spectral features of the objects one can improve the reliability of the identification process. However, huge increase in data created by hyperspectral imaging is usually prohibitive. To overcome the complexity problem, we propose a persistent air-to-ground target tracking system inspired by a state-of-the-art, adaptive, multi-modal sensor. The adaptive sensor is capable of providing panchromatic images as well as the spectra of desired pixels. This addresses the data challenge of hyperspectral tracking by only recording spectral data as needed. Spectral likelihoods are integrated into a data association algorithm in a Bayesian fashion to minimize the likelihood of misidentification. A framework for controlling spectral data collection is developed by incorporating motion segmentation information and prior information from a Gaussian Sum filter (GSF) movement predictions from a multi-model forecasting set. An intersection mask of the surveillance area is extracted from OpenStreetMap source and incorporated into the tracking algorithm to perform online refinement of multiple model set. The proposed system is tested using challenging and realistic scenarios generated in an adverse environment.

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

PubMed Central

Chang, Chi-Ying; Chang, Chia-Chi; Hsiao, Tzu-Chien

2013-01-01

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes. PMID:24240806

Hyperspectral Remote Sensing of Terrestrial Ecosystem Productivity from ISS

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Campbell, P. K. E.; Gao, B. C.; Flanagan, L. B.; Goulden, M.

2017-12-01

Data from the Hyperspectral Imager for Coastal Ocean (HICO), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. The ISS orbit introduces both limitations and opportunities for observing ecosystem dynamics. Twenty six HICO images were used from four study sites representing different vegetation types: grasslands, shrubland, and forest. Gross ecosystem production (GEP) data from eddy covariance were matched with HICO-derived spectra. Multiple algorithms were successful relating spectral reflectance with GEP, including: Spectral Vegetation Indices (SVI), SVI in a light use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to Multiband Hyperspectral Indices (MHI) from stepwise regressions and Partial Least Squares Regression (PLSR). Algorithms were able to achieve r2 better than 0.7 for both GEP at the overpass time and daily GEP. These algorithms were successful using a diverse set of observations combining data from multiple years, multiple times during growing season, different times of day, with different view angles, and different vegetation types. The demonstrated robustness of the algorithms presented in this study over these conditions provides some confidence in mapping spatial patterns of GEP, describing variability within fields as well as the regional patterns based only on spectral reflectance information. The ISS orbit provides periods with multiple observations collected at different times of the day within a period of a few days. Diurnal GEP patterns were estimated comparing the half-hourly average GEP from the flux tower against HICO estimates of GEP (r2=0.87) if morning, midday, and afternoon observations were available for average fluxes in the time period.

Spectral characterization of near-infrared acousto-optic tunable filter (AOTF) hyperspectral imaging systems using standard calibration materials.

PubMed

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2011-04-01

In this study, we propose and evaluate a method for spectral characterization of acousto-optic tunable filter (AOTF) hyperspectral imaging systems in the near-infrared (NIR) spectral region from 900 nm to 1700 nm. The proposed spectral characterization method is based on the SRM-2035 standard reference material, exhibiting distinct spectral features, which enables robust non-rigid matching of the acquired and reference spectra. The matching is performed by simultaneously optimizing the parameters of the AOTF tuning curve, spectral resolution, baseline, and multiplicative effects. In this way, the tuning curve (frequency-wavelength characteristics) and the corresponding spectral resolution of the AOTF hyperspectral imaging system can be characterized simultaneously. Also, the method enables simple spectral characterization of the entire imaging plane of hyperspectral imaging systems. The results indicate that the method is accurate and efficient and can easily be integrated with systems operating in diffuse reflection or transmission modes. Therefore, the proposed method is suitable for characterization, calibration, or validation of AOTF hyperspectral imaging systems. © 2011 Society for Applied Spectroscopy

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Neural Networks for Segregation of Multiple Objects: Visual Figure-Ground Separation and Auditory Pitch Perception.

NASA Astrophysics Data System (ADS)

Wyse, Lonce

An important component of perceptual object recognition is the segmentation into coherent perceptual units of the "blooming buzzing confusion" that bombards the senses. The work presented herein develops neural network models of some key processes of pre-attentive vision and audition that serve this goal. A neural network model, called an FBF (Feature -Boundary-Feature) network, is proposed for automatic parallel separation of multiple figures from each other and their backgrounds in noisy images. Figure-ground separation is accomplished by iterating operations of a Boundary Contour System (BCS) that generates a boundary segmentation of a scene, and a Feature Contour System (FCS) that compensates for variable illumination and fills-in surface properties using boundary signals. A key new feature is the use of the FBF filling-in process for the figure-ground separation of connected regions, which are subsequently more easily recognized. The new CORT-X 2 model is a feed-forward version of the BCS that is designed to detect, regularize, and complete boundaries in up to 50 percent noise. It also exploits the complementary properties of on-cells and off -cells to generate boundary segmentations and to compensate for boundary gaps during filling-in. In the realm of audition, many sounds are dominated by energy at integer multiples, or "harmonics", of a fundamental frequency. For such sounds (e.g., vowels in speech), the individual frequency components fuse, so that they are perceived as one sound source with a pitch at the fundamental frequency. Pitch is integral to separating auditory sources, as well as to speaker identification and speech understanding. A neural network model of pitch perception called SPINET (SPatial PItch NETwork) is developed and used to simulate a broader range of perceptual data than previous spectral models. The model employs a bank of narrowband filters as a simple model of basilar membrane mechanics, spectral on-center off-surround competitive interactions, and a "harmonic sieve" mechanism whereby the strength of a pitch depends only on spectral regions near harmonics. The model is evaluated using data involving mistuned components, shifted harmonics, complex tones with varying phase relationships, and continuous spectra such as rippled noise and narrow noise bands.

Discriminative illumination: per-pixel classification of raw materials based on optimal projections of spectral BRDF.

PubMed

Liu, Chao; Gu, Jinwei

2014-01-01

Classifying raw, unpainted materials--metal, plastic, ceramic, fabric, and so on--is an important yet challenging task for computer vision. Previous works measure subsets of surface spectral reflectance as features for classification. However, acquiring the full spectral reflectance is time consuming and error-prone. In this paper, we propose to use coded illumination to directly measure discriminative features for material classification. Optimal illumination patterns--which we call "discriminative illumination"--are learned from training samples, after projecting to which the spectral reflectance of different materials are maximally separated. This projection is automatically realized by the integration of incident light for surface reflection. While a single discriminative illumination is capable of linear, two-class classification, we show that multiple discriminative illuminations can be used for nonlinear and multiclass classification. We also show theoretically that the proposed method has higher signal-to-noise ratio than previous methods due to light multiplexing. Finally, we construct an LED-based multispectral dome and use the discriminative illumination method for classifying a variety of raw materials, including metal (aluminum, alloy, steel, stainless steel, brass, and copper), plastic, ceramic, fabric, and wood. Experimental results demonstrate its effectiveness.

Functional Topography of Human Auditory Cortex

PubMed Central

Rauschecker, Josef P.

2016-01-01

Functional and anatomical studies have clearly demonstrated that auditory cortex is populated by multiple subfields. However, functional characterization of those fields has been largely the domain of animal electrophysiology, limiting the extent to which human and animal research can inform each other. In this study, we used high-resolution functional magnetic resonance imaging to characterize human auditory cortical subfields using a variety of low-level acoustic features in the spectral and temporal domains. Specifically, we show that topographic gradients of frequency preference, or tonotopy, extend along two axes in human auditory cortex, thus reconciling historical accounts of a tonotopic axis oriented medial to lateral along Heschl's gyrus and more recent findings emphasizing tonotopic organization along the anterior–posterior axis. Contradictory findings regarding topographic organization according to temporal modulation rate in acoustic stimuli, or “periodotopy,” are also addressed. Although isolated subregions show a preference for high rates of amplitude-modulated white noise (AMWN) in our data, large-scale “periodotopic” organization was not found. Organization by AM rate was correlated with dominant pitch percepts in AMWN in many regions. In short, our data expose early auditory cortex chiefly as a frequency analyzer, and spectral frequency, as imposed by the sensory receptor surface in the cochlea, seems to be the dominant feature governing large-scale topographic organization across human auditory cortex. SIGNIFICANCE STATEMENT In this study, we examine the nature of topographic organization in human auditory cortex with fMRI. Topographic organization by spectral frequency (tonotopy) extended in two directions: medial to lateral, consistent with early neuroimaging studies, and anterior to posterior, consistent with more recent reports. Large-scale organization by rates of temporal modulation (periodotopy) was correlated with confounding spectral content of amplitude-modulated white-noise stimuli. Together, our results suggest that the organization of human auditory cortex is driven primarily by its response to spectral acoustic features, and large-scale periodotopy spanning across multiple regions is not supported. This fundamental information regarding the functional organization of early auditory cortex will inform our growing understanding of speech perception and the processing of other complex sounds. PMID:26818527

Classification of independent components of EEG into multiple artifact classes.

PubMed

Frølich, Laura; Andersen, Tobias S; Mørup, Morten

2015-01-01

In this study, we aim to automatically identify multiple artifact types in EEG. We used multinomial regression to classify independent components of EEG data, selecting from 65 spatial, spectral, and temporal features of independent components using forward selection. The classifier identified neural and five nonneural types of components. Between subjects within studies, high classification performances were obtained. Between studies, however, classification was more difficult. For neural versus nonneural classifications, performance was on par with previous results obtained by others. We found that automatic separation of multiple artifact classes is possible with a small feature set. Our method can reduce manual workload and allow for the selective removal of artifact classes. Identifying artifacts during EEG recording may be used to instruct subjects to refrain from activity causing them. Copyright © 2014 Society for Psychophysiological Research.

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

PubMed

Samuel, Oluwarotimi Williams; Geng, Yanjuan; Li, Xiangxin; Li, Guanglin

2017-10-28

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Spectroscopic characterization of enzymatic flax retting: Factor analysis of FT-IR and FT-Raman data

NASA Astrophysics Data System (ADS)

Archibald, D. D.; Henrikssen, G.; Akin, D. E.; Barton, F. E.

1998-06-01

Flax retting is a chemical, microbial or enzymatic process which releases the bast fibers from the stem matrix so they can be suitable for mechanical processing before spinning into linen yarn. This study aims to determine the vibrational spectral features and sampling methods which can be used to evaluate the retting process. Flax stems were retted on a small scale using an enzyme mixture known to yield good retted flax. Processed stems were harvested at various time points in the process and the retting was evaluated by conventional methods including weight loss, color difference and Fried's test, a visual ranking of how the stems disintegrate in hot water. Spectroscopic measurements were performed on either whole stems or powders of the fibers that were mechanically extracted from the stems. Selected regions of spectra were baseline and amplitude corrected using a variant of the multiplicative signal correction method. Principal component regression and partial least-squares regression with full cross-validation were used to determine the spectral features and rate of spectral transformation by regressing the spectra against the retting time in hours. FT-Raman of fiber powders and FT-IR reflectance of whole stems were the simplest and most precise methods for monitoring the retting transformation. Raman tracks the retting by measuring the decrease in aromatic signal and subtle changes in the C-H stretching vibrations. The IR method uses complex spectral features in the fingerprint and carbonyl region, many of which are due to polysaccharide components. Both spectral techniques monitor the retting process with greater precision than the reference method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vargas, Asticio; Center for Optics and Photonics, Universidad de Concepción, Casilla 4016, Concepción; Mar Sánchez-López, María del

Multiple-beam Fabry-Perot (FP) interferences occur in liquid crystal retarders (LCR) devoid of an antireflective coating. In this work, a highly accurate method to obtain the spectral retardance of such devices is presented. On the basis of a simple model of the LCR that includes FP effects and by using a voltage transfer function, we show how the FP features in the transmission spectrum can be used to accurately retrieve the ordinary and extraordinary spectral phase delays, and the voltage dependence of the latter. As a consequence, the modulation characteristics of the device are fully determined with high accuracy by meansmore » of a few off-state physical parameters which are wavelength-dependent, and a single voltage transfer function that is valid within the spectral range of characterization.« less

Identification of Hydrated Sulfates Collected in the Northern Rio Tinto Valley by Reflectance and Raman Spectroscopy

NASA Technical Reports Server (NTRS)

Chemtob, S. M.; Arvidson, R. E.; Fernandez-Remolar, D. C.; Amils, R.; Morris, R. V.; Ming, D. W.; Prieto-Ballesteros, O.; Mustard, J. F.; Hutchinson, L.; Stein, T. C.;

Parallel evolution of image processing tools for multispectral imagery

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Brumby, Steven P.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Szymanski, John J.; Bloch, Jeffrey J.

2000-11-01

We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI , covering the recent Cerro Grande fire at Los Alamos, NM, USA.

Design of a multispectral, wedge filter, remote-sensing instrument incorporating a multiport, thinned, CCD area array

NASA Astrophysics Data System (ADS)

Demro, James C.; Hartshorne, Richard; Woody, Loren M.; Levine, Peter A.; Tower, John R.

1995-06-01

The next generation Wedge Imaging Spectrometer (WIS) instruments currently in integration at Hughes SBRD incorporate advanced features to increase operation flexibility for remotely sensed hyperspectral imagery collection and use. These features include: a) multiple linear wedge filters to tailor the spectral bands to the scene phenomenology; b) simple, replaceable fore-optics to allow different spatial resolutions and coverages; c) data acquisition system (DAS) that collects the full data stream simultaneously from both WIS instruments (VNIR and SWIR/MWIR), stores the data in a RAID storage, and provides for down-loading of the data to MO disks; the WIS DAS also allows selection of the spectral band sets to be stored; d) high-performance VNIR camera subsystem based upon a 512 X 512 CCD area array and associated electronics.

Advanced processing and simulation of MRS data using the FID appliance (FID-A)-An open source, MATLAB-based toolkit.

PubMed

Simpson, Robin; Devenyi, Gabriel A; Jezzard, Peter; Hennessy, T Jay; Near, Jamie

2017-01-01

To introduce a new toolkit for simulation and processing of magnetic resonance spectroscopy (MRS) data, and to demonstrate some of its novel features. The FID appliance (FID-A) is an open-source, MATLAB-based software toolkit for simulation and processing of MRS data. The software is designed specifically for processing data with multiple dimensions (eg, multiple radiofrequency channels, averages, spectral editing dimensions). It is equipped with functions for importing data in the formats of most major MRI vendors (eg, Siemens, Philips, GE, Agilent) and for exporting data into the formats of several common processing software packages (eg, LCModel, jMRUI, Tarquin). This paper introduces the FID-A software toolkit and uses examples to demonstrate its novel features, namely 1) the use of a spectral registration algorithm to carry out useful processing routines automatically, 2) automatic detection and removal of motion-corrupted scans, and 3) the ability to perform several major aspects of the MRS computational workflow from a single piece of software. This latter feature is illustrated through both high-level processing of in vivo GABA-edited MEGA-PRESS MRS data, as well as detailed quantum mechanical simulations to generate an accurate LCModel basis set for analysis of the same data. All of the described processing steps resulted in a marked improvement in spectral quality compared with unprocessed data. Fitting of MEGA-PRESS data using a customized basis set resulted in improved fitting accuracy compared with a generic MEGA-PRESS basis set. The FID-A software toolkit enables high-level processing of MRS data and accurate simulation of in vivo MRS experiments. Magn Reson Med 77:23-33, 2017. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Sharply curved turn around duct flow predictions using spectral partitioning of the turbulent kinetic energy and a pressure modified wall law

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1986-01-01

Computational predictions of turbulent flow in sharply curved 180 degree turn around ducts are presented. The CNS2D computer code is used to solve the equations of motion for two-dimensional incompressible flows transformed to a nonorthogonal body-fitted coordinate system. This procedure incorporates the pressure velocity correction algorithm SIMPLE-C to iteratively solve a discretized form of the transformed equations. A multiple scale turbulence model based on simplified spectral partitioning is employed to obtain closure. Flow field predictions utilizing the multiple scale model are compared to features predicted by the traditional single scale k-epsilon model. Tuning parameter sensitivities of the multiple scale model applied to turn around duct flows are also determined. In addition, a wall function approach based on a wall law suitable for incompressible turbulent boundary layers under strong adverse pressure gradients is tested. Turn around duct flow characteristics utilizing this modified wall law are presented and compared to results based on a standard wall treatment.

Spectroscopy as a tool for geochemical modeling

NASA Astrophysics Data System (ADS)

Kopacková, Veronika; Chevrel, Stephane; Bourguignon, Anna

2011-11-01

This study focused on testing the feasibility of up-scaling ground-spectra-derived parameters to HyMap spectral and spatial resolution and whether they could be further used for a quantitative determination of the following geochemical parameters: As, pH and Clignite content. The study was carried on the Sokolov lignite mine as it represents a site with extreme material heterogeneity and high heavy-metal gradients. A new segmentation method based on the unique spectral properties of acid materials was developed and applied to the multi-line HyMap image data corrected for BRDF and atmospheric effects. The quantitative parameters were calculated for multiple absorption features identified within the VIS/VNIR/SWIR regions (simple band ratios, absorption band depth and quantitative spectral feature parameters calculated dynamically for each spectral measurement (centre of the absorption band (λ), depth of the absorption band (D), width of the absorption band (Width), and asymmetry of the absorption band (S)). The degree of spectral similarity between the ground and image spectra was assessed. The linear models for pH, As and the Clignite content of the whole and segmented images were cross-validated on the selected homogenous areas defined in the HS images using ground truth. For the segmented images, reliable results were achieved as follows: As: R2=0.84, Clignite: R2=0.88 and R2 pH: R2= 0.57.

Dual-band plasmonic resonator based on Jerusalem cross-shaped nanoapertures

NASA Astrophysics Data System (ADS)

Cetin, Arif E.; Kaya, Sabri; Mertiri, Alket; Aslan, Ekin; Erramilli, Shyamsunder; Altug, Hatice; Turkmen, Mustafa

2015-06-01

In this paper, we both experimentally and numerically introduce a dual-resonant metamaterial based on subwavelength Jerusalem cross-shaped apertures. We numerically investigate the physical origin of the dual-resonant behavior, originating from the constituting aperture elements, through finite difference time domain calculations. Our numerical calculations show that at the dual-resonances, the aperture system supports large and easily accessible local electromagnetic fields. In order to experimentally realize the aperture system, we utilize a high-precision and lift-off free fabrication method based on electron-beam lithography. We also introduce a fine-tuning mechanism for controlling the dual-resonant spectral response through geometrical device parameters. Finally, we show the aperture system's highly advantageous far- and near-field characteristics through numerical calculations on refractive index sensitivity. The quantitative analyses on the availability of the local fields supported by the aperture system are employed to explain the grounds behind the sensitivity of each spectral feature within the dual-resonant behavior. Possessing dual-resonances with large and accessible electromagnetic fields, Jerusalem cross-shaped apertures can be highly advantageous for wide range of applications demanding multiple spectral features with strong nearfield characteristics.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

Al-Khafaji, Suhad Lateef; Jun Zhou; Zia, Ali; Liew, Alan Wee-Chung

2018-02-01

Spectral-spatial feature extraction is an important task in hyperspectral image processing. In this paper we propose a novel method to extract distinctive invariant features from hyperspectral images for registration of hyperspectral images with different spectral conditions. Spectral condition means images are captured with different incident lights, viewing angles, or using different hyperspectral cameras. In addition, spectral condition includes images of objects with the same shape but different materials. This method, which is named spectral-spatial scale invariant feature transform (SS-SIFT), explores both spectral and spatial dimensions simultaneously to extract spectral and geometric transformation invariant features. Similar to the classic SIFT algorithm, SS-SIFT consists of keypoint detection and descriptor construction steps. Keypoints are extracted from spectral-spatial scale space and are detected from extrema after 3D difference of Gaussian is applied to the data cube. Two descriptors are proposed for each keypoint by exploring the distribution of spectral-spatial gradient magnitude in its local 3D neighborhood. The effectiveness of the SS-SIFT approach is validated on images collected in different light conditions, different geometric projections, and using two hyperspectral cameras with different spectral wavelength ranges and resolutions. The experimental results show that our method generates robust invariant features for spectral-spatial image matching.

Temporal Evolution of Ion Spectral Structures During a Geomagnetic Storm: Observations and Modeling

NASA Astrophysics Data System (ADS)

Ferradas, C. P.; Zhang, J.-C.; Spence, H. E.; Kistler, L. M.; Larsen, B. A.; Reeves, G. D.; Skoug, R. M.; Funsten, H. O.

2018-01-01

Using the Van Allen Probes/Helium, Oxygen, Proton, and Electron mass spectrometer, we perform a case study of the temporal evolution of ion spectral structures observed in the energy range of 1 to 50 keV throughout the geomagnetic storm of 2 October 2013. The ion spectral features are observed near the inner edge of the plasma sheet and are signatures of fresh transport from the plasma sheet into the inner magnetosphere. We find that the characteristics of the ion structures are determined by the intensity of the convection electric field. Prior to the beginning of the storm, the plasma sheet inner edge exhibits narrow nose spectral structures that vary little in energy across L values. Ion access to the inner magnetosphere during these times is limited to the nose energy bands. As convection is enhanced and large amounts of plasma are injected from the plasma sheet during the main phase of the storm, ion access occurs at a wide energy range, as no nose structures are observed. As the magnetosphere recovers from the storm, single noses and then multiple noses are observed once again. We use a model of ion drift and losses due to charge exchange to simulate the ion spectra and gain insight into the main observed features.

Multigigahertz range-Doppler correlative processing in crystals

NASA Astrophysics Data System (ADS)

Harris, Todd L.; Babbitt, Wm. R.; Merkel, Kristian D.; Mohan, R. Krishna; Cole, Zachary; Olson, Andy

2004-06-01

Spectral-spatial holographic crystals have the unique ability to resolve fine spectral features (down to kilohertz) in an optical waveform over a broad bandwidth (over 10 gigahertz). This ability allows these crystals to record the spectral interference between spread spectrum waveforms that are temporally separated by up to several microseconds. Such crystals can be used for performing radar range-Doppler processing with fine temporal resolution. An added feature of these crystals is the long upper state lifetime of the absorbing rare earth ions, which allows the coherent integration of multiple recorded spectra, yielding integration gain and significant processing gain enhancement for selected code sets, as well as high resolution Doppler processing. Parallel processing of over 10,000 beams could be achieved with a crystal the size of a sugar cube. Spectral-spatial holographic processing and coherent integration of up to 2.5 Gigabit per second coded waveforms and of lengths up to 2047 bits has previously been reported. In this paper, we present the first demonstration of Doppler processing with these crystals. Doppler resolution down to a few hundred Hz for broadband radar signals can be achieved. The processing can be performed directly on signals modulated onto IF carriers (up to several gigahertz) without having to mix the signals down to baseband and without having to employ broadband analog to digital conversion.

Temporal evolution of ion spectral structures during a geomagnetic storm: Observations and modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferradas Alva, Cristian Pablo; Zhang, J.-C.; Spence, H. E.

Using the Van Allen Probes/Helium, Oxygen, Proton, and Electron (HOPE) mass spectrometer, we perform a case study of the temporal evolution of ion spectral structures observed in the energy range of 1- ~50 keV throughout the geomagnetic storm of 2 October 2013. The ion spectral features are observed near the inner edge of the plasma sheet and are signatures of fresh transport from the plasma sheet into the inner magnetosphere. We find that the characteristics of the ion structures are determined by the intensity of the convection electric field. Prior to the beginning of the storm, the plasma sheet innermore » edge exhibits narrow nose spectral structures that vary little in energy across L values. Ion access to the inner magnetosphere during these times is limited to the nose energy bands. As convection is enhanced and large amounts of plasma are injected from the plasma sheet during the main phase of the storm, ion access occurs at a wide energy range, as no nose structures are observed. Here, as the magnetosphere recovers from the storm, single noses and then multiple noses are observed once again. Lastly, we use a model of ion drift and losses due to charge exchange to simulate the ion spectra and gain insight into the main observed features.« less

Temporal evolution of ion spectral structures during a geomagnetic storm: Observations and modeling

DOE PAGES

Ferradas Alva, Cristian Pablo; Zhang, J.-C.; Spence, H. E.; ...

2017-12-13

Using the Van Allen Probes/Helium, Oxygen, Proton, and Electron (HOPE) mass spectrometer, we perform a case study of the temporal evolution of ion spectral structures observed in the energy range of 1- ~50 keV throughout the geomagnetic storm of 2 October 2013. The ion spectral features are observed near the inner edge of the plasma sheet and are signatures of fresh transport from the plasma sheet into the inner magnetosphere. We find that the characteristics of the ion structures are determined by the intensity of the convection electric field. Prior to the beginning of the storm, the plasma sheet innermore » edge exhibits narrow nose spectral structures that vary little in energy across L values. Ion access to the inner magnetosphere during these times is limited to the nose energy bands. As convection is enhanced and large amounts of plasma are injected from the plasma sheet during the main phase of the storm, ion access occurs at a wide energy range, as no nose structures are observed. Here, as the magnetosphere recovers from the storm, single noses and then multiple noses are observed once again. Lastly, we use a model of ion drift and losses due to charge exchange to simulate the ion spectra and gain insight into the main observed features.« less

Altered rock spectra in the visible and near infrared. [western Nevada

NASA Technical Reports Server (NTRS)

Hunt, G. R.; Ashley, R. P. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Visible and near-infrared (0.35 to 2.5 micron m) bidirectional reflection spectra recorded for a suite of well-characterized hydrothermally altered rock samples typically display well defined bands caused by both electronic and vibrational processes in the individual mineral constituents. Electronic transitions in the iron-bearing constituent minerals produce diagnostic minima near 0.43, 0.65, 0.85, and 0.93 micron m. Vibrational transitions in clay and water-bearing mineral constituents produce characteristic single or multiple features over limited spectral ranges near 1.4, 1.75, 1.9, 2.2, and 2.35 micron m. The most abundant feature-producing minerals present in these rocks are hematite, goethite, and alunite. Others frequently present are jarosite, kaolinite, potassium micas, pyrophyllite, montmorillonite, diaspore, and gypsum. The spectral region near 2.2 micron m is particularly important for detecting altered rocks by remote sensing.

BCI Competition IV – Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery Detection

PubMed Central

Zhang, Haihong; Guan, Cuntai; Ang, Kai Keng; Wang, Chuanchu

2012-01-01

Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set. PMID:22347153

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Detecting bursts in the EEG of very and extremely premature infants using a multi-feature approach.

PubMed

O'Toole, John M; Boylan, Geraldine B; Lloyd, Rhodri O; Goulding, Robert M; Vanhatalo, Sampsa; Stevenson, Nathan J

2017-07-01

To develop a method that segments preterm EEG into bursts and inter-bursts by extracting and combining multiple EEG features. Two EEG experts annotated bursts in individual EEG channels for 36 preterm infants with gestational age < 30 weeks. The feature set included spectral, amplitude, and frequency-weighted energy features. Using a consensus annotation, feature selection removed redundant features and a support vector machine combined features. Area under the receiver operator characteristic (AUC) and Cohen's kappa (κ) evaluated performance within a cross-validation procedure. The proposed channel-independent method improves AUC by 4-5% over existing methods (p < 0.001, n=36), with median (95% confidence interval) AUC of 0.989 (0.973-0.997) and sensitivity-specificity of 95.8-94.4%. Agreement rates between the detector and experts' annotations, κ=0.72 (0.36-0.83) and κ=0.65 (0.32-0.81), are comparable to inter-rater agreement, κ=0.60 (0.21-0.74). Automating the visual identification of bursts in preterm EEG is achievable with a high level of accuracy. Multiple features, combined using a data-driven approach, improves on existing single-feature methods. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Random-Forest Classification of High-Resolution Remote Sensing Images and Ndsm Over Urban Areas

NASA Astrophysics Data System (ADS)

Sun, X. F.; Lin, X. G.

2017-09-01

As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample's category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.

IMAGE 100: The interactive multispectral image processing system

NASA Technical Reports Server (NTRS)

Schaller, E. S.; Towles, R. W.

1975-01-01

The need for rapid, cost-effective extraction of useful information from vast quantities of multispectral imagery available from aircraft or spacecraft has resulted in the design, implementation and application of a state-of-the-art processing system known as IMAGE 100. Operating on the general principle that all objects or materials possess unique spectral characteristics or signatures, the system uses this signature uniqueness to identify similar features in an image by simultaneously analyzing signatures in multiple frequency bands. Pseudo-colors, or themes, are assigned to features having identical spectral characteristics. These themes are displayed on a color CRT, and may be recorded on tape, film, or other media. The system was designed to incorporate key features such as interactive operation, user-oriented displays and controls, and rapid-response machine processing. Owing to these features, the user can readily control and/or modify the analysis process based on his knowledge of the input imagery. Effective use can be made of conventional photographic interpretation skills and state-of-the-art machine analysis techniques in the extraction of useful information from multispectral imagery. This approach results in highly accurate multitheme classification of imagery in seconds or minutes rather than the hours often involved in processing using other means.

Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features.

PubMed

Khushaba, Rami N; Takruri, Maen; Miro, Jaime Valls; Kodagoda, Sarath

2014-07-01

Recent studies in Electromyogram (EMG) pattern recognition reveal a gap between research findings and a viable clinical implementation of myoelectric control strategies. One of the important factors contributing to the limited performance of such controllers in practice is the variation in the limb position associated with normal use as it results in different EMG patterns for the same movements when carried out at different positions. However, the end goal of the myoelectric control scheme is to allow amputees to control their prosthetics in an intuitive and accurate manner regardless of the limb position at which the movement is initiated. In an attempt to reduce the impact of limb position on EMG pattern recognition, this paper proposes a new feature extraction method that extracts a set of power spectrum characteristics directly from the time-domain. The end goal is to form a set of features invariant to limb position. Specifically, the proposed method estimates the spectral moments, spectral sparsity, spectral flux, irregularity factor, and signals power spectrum correlation. This is achieved through using Fourier transform properties to form invariants to amplification, translation and signal scaling, providing an efficient and accurate representation of the underlying EMG activity. Additionally, due to the inherent temporal structure of the EMG signal, the proposed method is applied on the global segments of EMG data as well as the sliced segments using multiple overlapped windows. The performance of the proposed features is tested on EMG data collected from eleven subjects, while implementing eight classes of movements, each at five different limb positions. Practical results indicate that the proposed feature set can achieve significant reduction in classification error rates, in comparison to other methods, with ≈8% error on average across all subjects and limb positions. A real-time implementation and demonstration is also provided and made available as a video supplement (see Appendix A). Copyright © 2014 Elsevier Ltd. All rights reserved.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery

NASA Astrophysics Data System (ADS)

Wang, Ke; Guo, Ping; Luo, A.-Li

2017-03-01

Spectral feature extraction is a crucial procedure in automated spectral analysis. This procedure starts from the spectral data and produces informative and non-redundant features, facilitating the subsequent automated processing and analysis with machine-learning and data-mining techniques. In this paper, we present a new automated feature extraction method for astronomical spectra, with application in spectral classification and defective spectra recovery. The basic idea of our approach is to train a deep neural network to extract features of spectra with different levels of abstraction in different layers. The deep neural network is trained with a fast layer-wise learning algorithm in an analytical way without any iterative optimization procedure. We evaluate the performance of the proposed scheme on real-world spectral data. The results demonstrate that our method is superior regarding its comprehensive performance, and the computational cost is significantly lower than that for other methods. The proposed method can be regarded as a new valid alternative general-purpose feature extraction method for various tasks in spectral data analysis.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

Voyager 1 imaging and IRIS observations of Jovian methane absorption and thermal emission: Implications for cloud structure

NASA Technical Reports Server (NTRS)

West, R. A.; Kupferman, P. N.; Hart, H.

1984-01-01

Images from three filters of the Voyager 1 wide angle camera are used to measure the continuum reflectivity and spectral gradient near 6000 A and the 6190 A band methane/continuum ratio for a variety of cloud features in Jupiter's atmosphere. The dark barge features in the North Equatorial Belt have anomalously strong positive continuum spectral gradients suggesting unique composition. Methane absorption is shown at unprecedented spatial scales for the Great Red Spot and its immediate environment, for a dark barge feature in the North Equatorial Belt, and for two hot spot and plume regions in the North Equatorial Belt. Methane absorption and five micrometer emission are correlated in the vicinity of the Great Red Spot but are anticorrelated in one of the plume hot spot regions. Methane absorption and simultaneous maps of five micrometer brightness temperature is quantitatively compared to realistic cloud structure models which include multiple scattering at five micrometer as well as in the visible. Variability in H2 quadrupole lines are also investigated.

Voyager 1 imaging and IRIS observations of Jovian methane absorption and thermal emission - Implications for cloud structure

NASA Technical Reports Server (NTRS)

West, R. A.; Kupferman, P. N.; Hart, H.

1985-01-01

Images from three filters of the Voyager 1 wide angle camera are used to measure the continuum reflectivity and spectral gradient near 6000 A and the 6190 A band methane/continuum ratio for a variety of cloud features in Jupiter's atmosphere. The dark barge features in the North Equatorial Belt have anomalously strong positive continuum spectral gradients suggesting unique composition. Methane absorption is shown at unprecedented spatial scales for the Great Red Spot and its immediate environment, for a dark barge feature in the North Equatorial Belt, and for two hot spot and plume regions in the North Equatorial Belt. Methane absorption and five micrometer emission are correlated in the vicinity of the Great Red Spot but are anticorrelated in one of the plume hot spot regions. Methane absorption and simultaneous maps of five micrometer brightness temperature are quantitatively compared to realistic cloud structure models which include multiple scattering at five micrometer as well as in the visible. Variability in H2 quadrupole lines are also investigated.

Interrelating meteorite and asteroid spectra at UV-Vis-NIR wavelengths using novel multiple-scattering methods

NASA Astrophysics Data System (ADS)

Martikainen, Julia; Penttilä, Antti; Gritsevich, Maria; Muinonen, Karri

2017-10-01

Asteroids have remained mostly the same for the past 4.5 billion years, and provide us information on the origin, evolution and current state of the Solar System. Asteroids and meteorites can be linked by matching their respective reflectance spectra. This is difficult, because spectral features depend strongly on the surface properties, and meteorite surfaces are free of regolith dust present in asteroids. Furthermore, asteroid surfaces experience space weathering which affects their spectral features.We present a novel simulation framework for assessing the spectral properties of meteorites and asteroids and matching their reflectance spectra. The simulations are carried out by utilizing a light-scattering code that takes inhomogeneous waves into account and simulates light scattering by Gaussian-random-sphere particles large compared to the wavelength of the incident light. The code uses incoherent input and computes phase matrices by utilizing incoherent scattering matrices. Reflectance spectra are modeled by combining olivine, pyroxene, and iron, the most common materials that dominate the spectral features of asteroids and meteorites. Space weathering is taken into account by adding nanoiron into the modeled asteroid spectrum. The complex refractive indices needed for the simulations are obtained from existing databases, or derived using an optimization that utilizes our ray-optics code and the measured spectrum of the material.We demonstrate our approach by applying it to the reflectance spectrum of (4) Vesta and the reflectance spectrum of the Johnstown meteorite measured with the University of Helsinki integrating-sphere UV-Vis-NIR spectrometer.Acknowledgments. The research is funded by the ERC Advanced Grant No. 320773 (SAEMPL).

Voyager planetary radio astronomy studies

NASA Technical Reports Server (NTRS)

Staelin, David H.; Eikenberry, Stephen S.

1993-01-01

Analysis of nonthermal radio emission data obtained by the Planetary Radio Astronomy (PRA) spectrometers on the Voyager 1 and 2 spacecraft was performed. This PRA data provided unique insights into the radio emission characteristics of the outer planets because of PRA's unique spectral response below the terrestrial ionospheric plasma frequency and its unprecedented proximity to the source. Of those results which were documented or published, this final report surveys only the highlights and cites references for more complete discussions. Unpublished results for Uranus, Neptune, and theoretical Ionian current distributions are presented at greater length. The most important conclusion to be drawn from these observations is that banded spectral emission is common to the radio emission below 1-2 MHz observed from all four Jovian planets. In every case multiple spectral features evolve on time scales of seconds to minutes. To the extent these features drift in frequency, they appear never to cross one another. The Neptunian spectral features appear to drift little or not at all, their evolution consisting principally of waxing and waning. Since other evidence strongly suggests that most or all of this radio emission is occurring near the local magnetospheric electron cyclotron frequency, this implies that this emission preferentially occurs at certain continually changing planetary radii. It remains unknown why certain radii might be favored, unless radial electric field components or other means serve to differentiate radially the magnetospheric plasma density, particle energy vectors, or particle coherence. Calculation of the spatial distribution and intensity of the Io-generated magnetospheric currents are also presented; these currents may be limited principally by wave impedance and local field strengths.

Multimodal Broadband Vibrational Sum Frequency Generation (MM-BB-V-SFG) Spectrometer and Microscope.

PubMed

Lee, Christopher M; Kafle, Kabindra; Huang, Shixin; Kim, Seong H

2016-01-14

A broadband sum frequency generation (BB-SFG) spectrometer with multimodal (MM) capabilities was constructed, which could be routinely reconfigured for tabletop experiments in reflection, transmission, and total internal reflection (TIR) geometries, as well as microscopic imaging. The system was constructed using a Ti:sapphire amplifier (800 nm, pulse width = 85 fs, repetition rate = 2 kHz), an optical parameter amplification (OPA) system for production of broadband IR pulses tunable between 1000 and 4000 cm(-1), and two Fabry-Pérot etalons arranged in series for production of narrowband 800 nm pulses. The key feature allowing the MM operation was the nearly collinear alignment of the visible (fixed, 800 nm) and infrared (tunable, 1000-4000 cm(-1)) pulses which were spatially separated. Physical insights discussed in this paper include the comparison of spectral bandwidth produced with 40 and 85 fs pump beams, the improvement of spectral resolution using etalons, the SFG probe volume in bulk analysis, the normalization of SFG signals, the stitching of multiple spectral segments, and the operation in different modes for air/liquid and adsorbate/solid interfaces, bulk samples, as well as spectral imaging combined with principle component analysis (PCA). The SFG spectral features obtained with the MM-BB-SFG system were compared with those obtained with picosecond-scanning-SFG system and high-resolution BB-SFG system (HR-BB-SFG) for dimethyl sulfoxide, α-pinene, and various samples containing cellulose (purified commercial products, Cladophora cell wall, cotton and flax fibers, and onion epidermis cell wall).

Helium induced fine structure in the electronic spectra of anthracene derivatives doped into superfluid helium nanodroplets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pentlehner, D.; Slenczka, A., E-mail: alkwin.slenczka@chemie.uni-regensburg.de

2015-01-07

Electronic spectra of organic molecules doped into superfluid helium nanodroplets show characteristic features induced by the helium environment. Besides a solvent induced shift of the electronic transition frequency, in many cases, a spectral fine structure can be resolved for electronic and vibronic transitions which goes beyond the expected feature of a zero phonon line accompanied by a phonon wing as known from matrix isolation spectroscopy. The spectral shape of the zero phonon line and the helium induced phonon wing depends strongly on the dopant species. Phonon wings, for example, are reported ranging from single or multiple sharp transitions to broadmore » (Δν > 100 cm{sup −1}) diffuse signals. Despite the large number of example spectra in the literature, a quantitative understanding of the helium induced fine structure of the zero phonon line and the phonon wing is missing. Our approach is a systematic investigation of related molecular compounds, which may help to shed light on this key feature of microsolvation in superfluid helium droplets. This paper is part of a comparative study of the helium induced fine structure observed in electronic spectra of anthracene derivatives with particular emphasis on a spectrally sharp multiplet splitting at the electronic origin. In addition to previously discussed species, 9-cyanoanthracene and 9-chloroanthracene will be presented in this study for the first time.« less

Utilization of satellite data for inventorying prairie ponds and lakes

NASA Technical Reports Server (NTRS)

Work, E. A., Jr.; Gilmer, D. S.

1976-01-01

ERTS-1 data were used in mapping open surface water features in the glaciated prairies. Emphasis was placed on the recognition of these features based upon water's uniquely low radiance in a single near-infrared waveband. On the basis of these results, thematic maps and statistics relating to open surface water were obtained. In a related effort, the added information content of multiple spectral wavebands was used for discriminating surface water at a level of detail finer than the virtual resolution of the data. The basic theory of this technique and some preliminary results are described.

xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data.

PubMed

Uppal, Karan; Soltow, Quinlyn A; Strobel, Frederick H; Pittard, W Stephen; Gernert, Kim M; Yu, Tianwei; Jones, Dean P

2013-01-16

Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract m/z features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation. xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1) improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2) evaluate sample quality and feature consistency, 3) detect feature overlap between datasets, and 4) characterize high-resolution m/z matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites. xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.

Quantitative Reflectance Spectra of Solid Powders as a Function of Particle Size

DOE PAGES

Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong; ...

2015-05-19

We have recently developed vetted methods for obtaining quantitative infrared directional-hemispherical reflectance spectra using a commercial integrating sphere. In this paper, the effects of particle size on the spectral properties are analyzed for several samples such as ammonium sulfate, calcium carbonate, and sodium sulfate as well as one organic compound, lactose. We prepared multiple size fractions for each sample and confirmed the mean sizes using optical microscopy. Most species displayed a wide range of spectral behavior depending on the mean particle size. General trends of reflectance vs. particle size are observed such as increased albedo for smaller particles: for mostmore » wavelengths, the reflectivity drops with increased size, sometimes displaying a factor of 4 or more drop in reflectivity along with a loss of spectral contrast. In the longwave infrared, several species with symmetric anions or cations exhibited reststrahlen features whose amplitude was nearly invariant with particle size, at least for intermediate- and large-sized sample fractions; that is, > ~150 microns. Trends of other types of bands (Christiansen minima, transparency features) are also investigated as well as quantitative analysis of the observed relationship between reflectance vs. particle diameter.« less

Quantitative Reflectance Spectra of Solid Powders as a Function of Particle Size

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong

We have recently developed vetted methods for obtaining quantitative infrared directional-hemispherical reflectance spectra using a commercial integrating sphere. In this paper, the effects of particle size on the spectral properties are analyzed for several samples such as ammonium sulfate, calcium carbonate, and sodium sulfate as well as one organic compound, lactose. We prepared multiple size fractions for each sample and confirmed the mean sizes using optical microscopy. Most species displayed a wide range of spectral behavior depending on the mean particle size. General trends of reflectance vs. particle size are observed such as increased albedo for smaller particles: for mostmore » wavelengths, the reflectivity drops with increased size, sometimes displaying a factor of 4 or more drop in reflectivity along with a loss of spectral contrast. In the longwave infrared, several species with symmetric anions or cations exhibited reststrahlen features whose amplitude was nearly invariant with particle size, at least for intermediate- and large-sized sample fractions; that is, > ~150 microns. Trends of other types of bands (Christiansen minima, transparency features) are also investigated as well as quantitative analysis of the observed relationship between reflectance vs. particle diameter.« less

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Distributed acoustic cues for caller identity in macaque vocalization.

PubMed

Fukushima, Makoto; Doyle, Alex M; Mullarkey, Matthew P; Mishkin, Mortimer; Averbeck, Bruno B

2015-12-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured 'coo' call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral-temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call's fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized.

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

[The research on separating and extracting overlapping spectral feature lines in LIBS using damped least squares method].

PubMed

Wang, Yin; Zhao, Nan-jing; Liu, Wen-qing; Yu, Yang; Fang, Li; Meng, De-shuo; Hu, Li; Zhang, Da-hai; Ma, Min-jun; Xiao, Xue; Wang, Yu; Liu, Jian-guo

2015-02-01

In recent years, the technology of laser induced breakdown spectroscopy has been developed rapidly. As one kind of new material composition detection technology, laser induced breakdown spectroscopy can simultaneously detect multi elements fast and simply without any complex sample preparation and realize field, in-situ material composition detection of the sample to be tested. This kind of technology is very promising in many fields. It is very important to separate, fit and extract spectral feature lines in laser induced breakdown spectroscopy, which is the cornerstone of spectral feature recognition and subsequent elements concentrations inversion research. In order to realize effective separation, fitting and extraction of spectral feature lines in laser induced breakdown spectroscopy, the original parameters for spectral lines fitting before iteration were analyzed and determined. The spectral feature line of' chromium (Cr I : 427.480 nm) in fly ash gathered from a coal-fired power station, which was overlapped with another line(FeI: 427.176 nm), was separated from the other one and extracted by using damped least squares method. Based on Gauss-Newton iteration, damped least squares method adds damping factor to step and adjust step length dynamically according to the feedback information after each iteration, in order to prevent the iteration from diverging and make sure that the iteration could converge fast. Damped least squares method helps to obtain better results of separating, fitting and extracting spectral feature lines and give more accurate intensity values of these spectral feature lines: The spectral feature lines of chromium in samples which contain different concentrations of chromium were separated and extracted. And then, the intensity values of corresponding spectral lines were given by using damped least squares method and least squares method separately. The calibration curves were plotted, which showed the relationship between spectral line intensity values and chromium concentrations in different samples. And then their respective linear correlations were compared. The experimental results showed that the linear correlation of the intensity values of spectral feature lines and the concentrations of chromium in different samples, which was obtained by damped least squares method, was better than that one obtained by least squares method. And therefore, damped least squares method was stable, reliable and suitable for separating, fitting and extracting spectral feature lines in laser induced breakdown spectroscopy.

The correlated k-distribution technique as applied to the AVHRR channels

NASA Technical Reports Server (NTRS)

Kratz, David P.

1995-01-01

Correlated k-distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k-distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k-distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k-distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k-distribution's principal advantages is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system.

PubMed

Min, Jianliang; Wang, Ping; Hu, Jianfeng

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1-2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver.

Important Considerations When Using Hydroxyl Airglow Measurements to Determine Climate Trends of the Mesopause Region.

NASA Astrophysics Data System (ADS)

Burns, G.; French, J.

2007-05-01

Spectral calibrations, airglow and possibly auroral contaminations, solar and telluric absorption features and the selection of transition probabilities can all influence rotational temperatures derived from measurements of hydroxyl airglow intensities. Consideration and examples are given of these influences. Measurements and analyses are outlined for data checking that should be undertaken if a hydroxyl airglow data set is to be used to determine climate trends. Multiple spectral calibrations should be conducted throughout the observing period, with regular inter- comparisons to other calibration sources also required. Uncertainties in spectral calibrations should be expressed as a temperature equivalent. Sufficient spectral scans at maximum resolution should be obtained under all extreme observing conditions (at the lowest solar depression angle operated both morning and night, moon and cloud both separately and combined, aurora and under conditions of enhanced atomic oxygen airglow, and under clear sky conditions but with high atmospheric water vapour content) so that an uncertainty for the derived rotational temperatures can be determined for the established data selection criteria. Once the varying emission and absorption features for the hydroxyl region of interest at your site are understood for the observing site, then the spectral resolution of the observing instrument can be reduced to increase temporal resolution with reasonable confidence. This confidence should be tested by investigating the average rotational temperatures derived from all possible line intensity ratios under the extreme observing conditions noted. If a spectral-fitting rotational temperature determination is used, the residuals from the fit should be summed and similarly examined. Hydroxyl measurements provide a cost effective means of monitoring the temperature of the climate-sensitive mesopause region on an almost nightly basis. If care is taken, they provide a valuable data set for investigating climate change.

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

PubMed

Liu, Da; Li, Jianxun

2016-12-16

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

FOCUSR: Feature Oriented Correspondence using Spectral Regularization–A Method for Precise Surface Matching

PubMed Central

Lombaert, Herve; Grady, Leo; Polimeni, Jonathan R.; Cheriet, Farida

2013-01-01

Existing methods for surface matching are limited by the trade-off between precision and computational efficiency. Here we present an improved algorithm for dense vertex-to-vertex correspondence that uses direct matching of features defined on a surface and improves it by using spectral correspondence as a regularization. This algorithm has the speed of both feature matching and spectral matching while exhibiting greatly improved precision (distance errors of 1.4%). The method, FOCUSR, incorporates implicitly such additional features to calculate the correspondence and relies on the smoothness of the lowest-frequency harmonics of a graph Laplacian to spatially regularize the features. In its simplest form, FOCUSR is an improved spectral correspondence method that nonrigidly deforms spectral embeddings. We provide here a full realization of spectral correspondence where virtually any feature can be used as additional information using weights on graph edges, but also on graph nodes and as extra embedded coordinates. As an example, the full power of FOCUSR is demonstrated in a real case scenario with the challenging task of brain surface matching across several individuals. Our results show that combining features and regularizing them in a spectral embedding greatly improves the matching precision (to a sub-millimeter level) while performing at much greater speed than existing methods. PMID:23868776

Quantitative lithologic mapping in spectral ratio feature space - Volcanic, sedimentary and metamorphic terrains

NASA Technical Reports Server (NTRS)

Campos-Marquetti, Raul, Jr.; Rockwell, Barnaby

1990-01-01

The nature of spectral lithologic mapping is studied utilizing ratios centered around the wavelength means of TM imagery. Laboratory-derived spectra are analyzed to determine the two-dimensional relationships and distributions visible in spectral ratio feature space. The spectral distributions of various rocks and minerals in ratio feature space are found to be controlled by several spectrally dominant molecules. Three study areas were examined: Rawhide Mining District, Nevada; Manzano Mountains, New Mexico; and the Sevilleta Long Term Ecological Research site in New Mexico. It is shown that, in the comparison of two ratio plots of laboratory reflectance spectra, i.e., 0.66/0.485 micron versus 1.65/2.22 microns with those derived from TM data, several molecules spectrally dominate the reflectance characteristic of surface lithologic units. Utilizing the above ratio combination, two areas are successfully mapped based on their distribution in spectral ratio feature space.

Spectroscopic Diagnosis of Arsenic Contamination in Agricultural Soils

PubMed Central

Shi, Tiezhu; Liu, Huizeng; Chen, Yiyun; Fei, Teng; Wang, Junjie; Wu, Guofeng

2017-01-01

This study investigated the abilities of pre-processing, feature selection and machine-learning methods for the spectroscopic diagnosis of soil arsenic contamination. The spectral data were pre-processed by using Savitzky-Golay smoothing, first and second derivatives, multiplicative scatter correction, standard normal variate, and mean centering. Principle component analysis (PCA) and the RELIEF algorithm were used to extract spectral features. Machine-learning methods, including random forests (RF), artificial neural network (ANN), radial basis function- and linear function- based support vector machine (RBF- and LF-SVM) were employed for establishing diagnosis models. The model accuracies were evaluated and compared by using overall accuracies (OAs). The statistical significance of the difference between models was evaluated by using McNemar’s test (Z value). The results showed that the OAs varied with the different combinations of pre-processing, feature selection, and classification methods. Feature selection methods could improve the modeling efficiencies and diagnosis accuracies, and RELIEF often outperformed PCA. The optimal models established by RF (OA = 86%), ANN (OA = 89%), RBF- (OA = 89%) and LF-SVM (OA = 87%) had no statistical difference in diagnosis accuracies (Z < 1.96, p < 0.05). These results indicated that it was feasible to diagnose soil arsenic contamination using reflectance spectroscopy. The appropriate combination of multivariate methods was important to improve diagnosis accuracies. PMID:28471412

A New Method for Atmospheric Correction of MRO/CRISM Data.

NASA Astrophysics Data System (ADS)

Noe Dobrea, Eldar Z.; Dressing, C.; Wolff, M. J.

2009-09-01

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter (MRO) collects hyperspectral images from 0.362 to 3.92 μm at 6.55 nanometers/channel, and at a spatial resolution of 20 m/pixel. The 1-2.6 μm spectral range is often used to identify and map the distribution of hydrous minerals using mineralogically diagnostic bands at 1.4 μm, 1.9 μm, and 2 - 2.5 micron region. Atmospheric correction of the 2-μm CO2 band typically employs the same methodology applied to OMEGA data (Mustard et al., Nature 454, 2008): an atmospheric opacity spectrum, obtained from the ratio of spectra from the base to spectra from the peak of Olympus Mons, is rescaled for each spectrum in the observation to fit the 2-μm CO2 band, and is subsequently used to correct the data. Three important aspects are not considered in this correction: 1) absorptions due to water vapor are improperly accounted for, 2) the band-center of each channel shifts slightly with time, and 3) multiple scattering due to atmospheric aerosols is not considered. The second issue results in miss-registration of the sharp CO2 features in the 2-μm triplet, and hence poor atmospheric correction. This leads to the necessity to ratio all spectra using the spectrum of a spectrally "bland” region in each observation in order to distinguish features 1.9 μm. Here, we present an improved atmospheric correction method, which uses emission phase function (EPF) observations to correct for molecular opacity, and a discrete ordinate radiative transfer algorithm (DISORT - Stamnes et al., Appl. Opt. 27, 1988) to correct for the effects of multiple scattering. This method results in a significant improvement in the correction of the 2-μm CO2 band, allowing us to forgo the use of spectral ratios that affect the spectral shape and preclude the derivation of reflectance values in the data.

Spectroscopic study of the dehydration and/or dehydroxylation of phyllosilicate and zeolite minerals

NASA Astrophysics Data System (ADS)

Che, Congcong; Glotch, Timothy D.; Bish, David L.; Michalski, Joseph R.; Xu, Wenqian

2011-05-01

Phyllosilicates on Mars mapped by infrared spectroscopic techniques could have been affected by dehydration and/or dehydroxylation associated with chemical weathering in hyperarid conditions, volcanism or shock heating associated with meteor impact. The effects of heat-induced dehydration and/or dehydroxylation on the infrared spectra of 14 phyllosilicates from four structural groups (kaolinite, smectite, sepiolite-palygorskite, and chlorite) and two natural zeolites are reported here. Pressed powders of size-separated phyllosilicate and natural zeolite samples were heated incrementally from 100°C to 900°C, cooled to room temperature, and measured using multiple spectroscopic techniques: midinfrared (400-4000 cm-1) attenuated total reflectance, midinfrared reflectance (400-1400 cm-1), and far-infrared reflectance (50-600 cm-1) spectroscopies. Correlated thermogravimetric analysis and X-ray diffraction data were also acquired in order to clarify the thermal transformation of each sample. For phyllosilicate samples, the OH stretching (˜3600 cm-1), OH bending (˜590-950 cm-1), and/or H2O bending (˜1630 cm-1) bands all become very weak or completely disappear upon heating to temperatures > 500°C. The spectral changes associated with SiO4 vibrations (˜1000 cm-1 and ˜500 cm-1) show large variations depending on the compositions and structures of phyllosilicates. The thermal behavior of phyllosilicate IR spectra is also affected by the type of octahedral cations. For example, spectral features of Al3+-rich smectites are more stable than those of Fe3+-rich smectites. The high-temperature (>800°C) spectral changes of trioctahedral Mg2+-rich phyllosilicates such as hectorite, saponite, and sepiolite result primarily from crystallization of enstatite. Phyllosilicates with moderate Mg2+ concentration (e.g., palygorskite, clinochlore) and dioctahedral montmorillonites (e.g., SAz-1 and SCa-3) with partial Mg2+-for-Al3+ substitution all have new spectral feature developed at ˜900 cm-1 upon heating to 800°C. Compared with phyllosilicates, spectral features of two natural zeolites, clinoptilolite and mordenite, are less affected by thermal treatments. Even after heating to 900°C, the IR spectral features attributed to Si (Al)-O stretching and bending vibration modes do not show significant differences from those of unheated zeolites.

Attosecond transient absorption probing of electronic superpositions of bound states in neon. Detection of quantum beats

DOE PAGES

Beck, Annelise R; Bernhardt, Birgitta; Warrick, Erika R.; ...

2014-11-07

Electronic wavepackets composed of multiple bound excited states of atomic neon lying between 19.6 and 21.5 eV are launched using an isolated attosecond pulse. Individual quantum beats of the wavepacket are detected by perturbing the induced polarization of the medium with a time-delayed few-femtosecond near-infrared (NIR) pulse via coupling the individual states to multiple neighboring levels. All of the initially excited states are monitored simultaneously in the attosecond transient absorption spectrum, revealing Lorentzian to Fano lineshape spectral changes as well as quantum beats. The most prominent beating of the several that were observed was in the spin–orbit split 3d absorptionmore » features, which has a 40 femtosecond period that corresponds to the spin–orbit splitting of 0.1 eV. The few-level models and multilevel calculations confirm that the observed magnitude of oscillation depends strongly on the spectral bandwidth and tuning of the NIR pulse and on the location of possible coupling states.« less

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Feature Transformation Detection Method with Best Spectral Band Selection Process for Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike; Brickhouse, Mark

2015-11-01

We present a newly developed feature transformation (FT) detection method for hyper-spectral imagery (HSI) sensors. In essence, the FT method, by transforming the original features (spectral bands) to a different feature domain, may considerably increase the statistical separation between the target and background probability density functions, and thus may significantly improve the target detection and identification performance, as evidenced by the test results in this paper. We show that by differentiating the original spectral, one can completely separate targets from the background using a single spectral band, leading to perfect detection results. In addition, we have proposed an automated best spectral band selection process with a double-threshold scheme that can rank the available spectral bands from the best to the worst for target detection. Finally, we have also proposed an automated cross-spectrum fusion process to further improve the detection performance in lower spectral range (<1000 nm) by selecting the best spectral band pair with multivariate analysis. Promising detection performance has been achieved using a small background material signature library for concept-proving, and has then been further evaluated and verified using a real background HSI scene collected by a HYDICE sensor.

Integration of heterogeneous features for remote sensing scene classification

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Restricted amide rotation with steric hindrance induced multiple conformations

NASA Astrophysics Data System (ADS)

Krishnan, V. V.; Vazquez, Salvador; Maitra, Kalyani; Maitra, Santanu

2017-12-01

The Csbnd N bond character is dependent directly upon the resonance-contributor structure population driven by the delocalized nitrogen lone-pair of electrons. In the case of N, N-dibenzyl-ortho-toluamide (o-DBET), the molecule adopts subpopulations of conformers with distinct NMR spectral features, particularly at low temperatures. This conformational adaptation is unique to o-DBET, while the corresponding meta- and para- forms do not show such behavior. Variable-temperature (VT) NMR, two-dimensional exchange spectroscopy (EXSY), and qualitative molecular modeling studies are used to demonstrate how multiple competing interactions such as restricted amide rotation and steric hindrance effects can lead to versatile molecular adaptations in the solution state.

Improved phase sensitivity in spectral domain phase microscopy using line-field illumination and self phase-referencing

PubMed Central

Yaqoob, Zahid; Choi, Wonshik; Oh, Seungeun; Lue, Niyom; Park, Yongkeun; Fang-Yen, Christopher; Dasari, Ramachandra R.; Badizadegan, Kamran; Feld, Michael S.

2010-01-01

We report a quantitative phase microscope based on spectral domain optical coherence tomography and line-field illumination. The line illumination allows self phase-referencing method to reject common-mode phase noise. The quantitative phase microscope also features a separate reference arm, permitting the use of high numerical aperture (NA > 1) microscope objectives for high resolution phase measurement at multiple points along the line of illumination. We demonstrate that the path-length sensitivity of the instrument can be as good as 41 pm/Hz, which makes it suitable for nanometer scale study of cell motility. We present the detection of natural motions of cell surface and two-dimensional surface profiling of a HeLa cell. PMID:19550464

A parametric multiclass Bayes error estimator for the multispectral scanner spatial model performance evaluation

NASA Technical Reports Server (NTRS)

Mobasseri, B. G.; Mcgillem, C. D.; Anuta, P. E. (Principal Investigator)

1978-01-01

The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.

A minimum drives automatic target definition procedure for multi-axis random control testing

NASA Astrophysics Data System (ADS)

Musella, Umberto; D'Elia, Giacomo; Carrella, Alex; Peeters, Bart; Mucchi, Emiliano; Marulo, Francesco; Guillaume, Patrick

2018-07-01

Multiple-Input Multiple-Output (MIMO) vibration control tests are able to closely replicate, via shakers excitation, the vibration environment that a structure needs to withstand during its operational life. This feature is fundamental to accurately verify the experienced stress state, and ultimately the fatigue life, of the tested structure. In case of MIMO random tests, the control target is a full reference Spectral Density Matrix in the frequency band of interest. The diagonal terms are the Power Spectral Densities (PSDs), representative for the acceleration operational levels, and the off-diagonal terms are the Cross Spectral Densities (CSDs). The specifications of random vibration tests are however often given in terms of PSDs only, coming from a legacy of single axis testing. Information about the CSDs is often missing. An accurate definition of the CSD profiles can further enhance the MIMO random testing practice, as these terms influence both the responses and the shaker's voltages (the so-called drives). The challenges are linked to the algebraic constraint that the full reference matrix must be positive semi-definite in the entire bandwidth, with no flexibility in modifying the given PSDs. This paper proposes a newly developed method that automatically provides the full reference matrix without modifying the PSDs, considered as test specifications. The innovative feature is the capability of minimizing the drives required to match the reference PSDs and, at the same time, to directly guarantee that the obtained full matrix is positive semi-definite. The drives minimization aims on one hand to reach the fixed test specifications without stressing the delicate excitation system; on the other hand it potentially allows to further increase the test levels. The detailed analytic derivation and implementation steps of the proposed method are followed by real-life testing considering different scenarios.

Research on hyperspectral dynamic scene and image sequence simulation

NASA Astrophysics Data System (ADS)

Sun, Dandan; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

2016-10-01

This paper presents a simulation method of hyper-spectral dynamic scene and image sequence for hyper-spectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyper-spectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyper-spectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyper-spectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyper-spectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyper-spectral images are consistent with the theoretical analysis results.

Particle Acceleration in Two Converging Shocks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Xin; Wang, Na; Shan, Hao

2017-06-20

Observations by spacecraft such as ACE , STEREO , and others show that there are proton spectral “breaks” with energy E {sub br} at 1–10 MeV in some large CME-driven shocks. Generally, a single shock with the diffusive acceleration mechanism would not predict the “broken” energy spectrum. The present paper focuses on two converging shocks to identify this energy spectral feature. In this case, the converging shocks comprise one forward CME-driven shock on 2006 December 13 and another backward Earth bow shock. We simulate the detailed particle acceleration processes in the region of the converging shocks using the Monte Carlomore » method. As a result, we not only obtain an extended energy spectrum with an energy “tail” up to a few 10 MeV higher than that in previous single shock model, but also we find an energy spectral “break” occurring on ∼5.5 MeV. The predicted energy spectral shape is consistent with observations from multiple spacecraft. The spectral “break,” then, in this case is caused by the interaction between the CME shock and Earth’s bow shock, and otherwise would not be present if Earth were not in the path of the CME.« less

Fatigue crack detection by nonlinear spectral correlation with a wideband input

NASA Astrophysics Data System (ADS)

Liu, Peipei; Sohn, Hoon

2017-04-01

Due to crack-induced nonlinearity, ultrasonic wave can distort, create accompanying harmonics, multiply waves of different frequencies, and, under resonance conditions, change resonance frequencies as a function of driving amplitude. All these nonlinear ultrasonic features have been widely studied and proved capable of detecting fatigue crack at its very early stage. However, in noisy environment, the nonlinear features might be drown in the noise, therefore it is difficult to extract those features using a conventional spectral density function. In this study, nonlinear spectral correlation is defined as a new nonlinear feature, which considers not only nonlinear modulations in ultrasonic waves but also spectral correlation between the nonlinear modulations. The proposed nonlinear feature is associated with the following two advantages: (1) stationary noise in the ultrasonic waves has little effect on nonlinear spectral correlation; and (2) the contrast of nonlinear spectral correlation between damage and intact conditions can be enhanced simply by using a wideband input. To validate the proposed nonlinear feature, micro fatigue cracks are introduced to aluminum plates by repeated tensile loading, and the experiment is conducted using surface-mounted piezoelectric transducers for ultrasonic wave generation and measurement. The experimental results confirm that the nonlinear spectral correlation can successfully detect fatigue crack with a higher sensitivity than the classical nonlinear coefficient.

Hyperspectral imaging using novel LWIR OPO for hazardous material detection and identification

NASA Astrophysics Data System (ADS)

Ruxton, Keith; Robertson, Gordon; Miller, Bill; Malcolm, Graeme P. A.; Maker, Gareth T.

2014-05-01

Current stand-off hyperspectral imaging detection solutions that operate in the mid-wave infrared (MWIR), nominally 2.5 - 5 μm spectral region, are limited by the number of absorption bands that can be addressed. This issue is most apparent when evaluating a scene with multiple absorbers with overlapping spectral features making accurate material identification challenging. This limitation can be overcome by moving to the long wave IR (LWIR) region, which is rich in characteristic absorption features, which can provide ample molecular information in order to perform presumptive identification relative to a spectral library. This work utilises an instrument platform to perform negative contrast imaging using a novel LWIR optical parametric oscillator (OPO) as the source. The OPO offers continuous tuning in the region 5.5 - 9.5 μm, which includes a number of molecular vibrations associated with the target material compositions. Scanning the scene of interest whilst sweeping the wavelength of the OPO emission will highlight the presence of a suspect material and by analysing the resulting absorption spectrum, presumptive identification is possible. This work presents a selection of initial results using the LWIR hyperspectral imaging platform on a range of white powder materials to highlight the benefit operating in the LWIR region compared to the MWIR.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

Orbital evidence for clay and acidic sulfate assemblages on Mars based on mineralogical analogs from Rio Tinto, Spain

NASA Astrophysics Data System (ADS)

Kaplan, Hannah H.; Milliken, Ralph E.; Fernández-Remolar, David; Amils, Ricardo; Robertson, Kevin; Knoll, Andrew H.

2016-09-01

Outcrops of hydrated minerals are widespread across the surface of Mars, with clay minerals and sulfates being commonly identified phases. Orbitally-based reflectance spectra are often used to classify these hydrated components in terms of a single mineralogy, although most surfaces likely contain multiple minerals that have the potential to record local geochemical conditions and processes. Reflectance spectra for previously identified deposits in Ius and Melas Chasma within the Valles Marineris, Mars, exhibit an enigmatic feature with two distinct absorptions between 2.2 and 2.3 μm. This spectral 'doublet' feature is proposed to result from a mixture of hydrated minerals, although the identity of the minerals has remained ambiguous. Here we demonstrate that similar spectral doublet features are observed in airborne, field, and laboratory reflectance spectra of rock and sediment samples from Rio Tinto, Spain. Combined visible-near infrared reflectance spectra and X-ray diffraction measurements of these samples reveal that the doublet feature arises from a mixture of Al-phyllosilicate (illite or muscovite) and jarosite. Analyses of orbital data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) shows that the martian spectral equivalents are also consistent with mixtures of Al-phyllosilicates and jarosite, where the Al-phyllosilicate may also include kaolinite and/or halloysite. A case study for a region within Ius Chasma demonstrates that the relative proportions of the Al-phyllosilicate(s) and jarosite vary within one stratigraphic unit as well as between stratigraphic units. The former observation suggests that the jarosite may be a diagenetic (authigenic) product and thus indicative of local pH and redox conditions, whereas the latter observation may be consistent with variations in sediment flux and/or fluid chemistry during sediment deposition.

Multiple copies of genes coding for electron transport proteins in the bacterium Nitrosomonas europaea.

PubMed

McTavish, H; LaQuier, F; Arciero, D; Logan, M; Mundfrom, G; Fuchs, J A; Hooper, A B

1993-04-01

The genome of Nitrosomonas europaea contains at least three copies each of the genes coding for hydroxylamine oxidoreductase (HAO) and cytochrome c554. A copy of an HAO gene is always located within 2.7 kb of a copy of a cytochrome c554 gene. Cytochrome P-460, a protein that shares very unusual spectral features with HAO, was found to be encoded by a gene separate from the HAO genes.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system

PubMed Central

Min, Jianliang; Wang, Ping

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1–2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver. PMID:29220351

Classification of fresh and frozen-thawed pork muscles using visible and near infrared hyperspectral imaging and textural analysis.

PubMed

Pu, Hongbin; Sun, Da-Wen; Ma, Ji; Cheng, Jun-Hu

2015-01-01

The potential of visible and near infrared hyperspectral imaging was investigated as a rapid and nondestructive technique for classifying fresh and frozen-thawed meats by integrating critical spectral and image features extracted from hyperspectral images in the region of 400-1000 nm. Six feature wavelengths (400, 446, 477, 516, 592 and 686 nm) were identified using uninformative variable elimination and successive projections algorithm. Image textural features of the principal component images from hyperspectral images were obtained using histogram statistics (HS), gray level co-occurrence matrix (GLCM) and gray level-gradient co-occurrence matrix (GLGCM). By these spectral and textural features, probabilistic neural network (PNN) models for classification of fresh and frozen-thawed pork meats were established. Compared with the models using the optimum wavelengths only, optimum wavelengths with HS image features, and optimum wavelengths with GLCM image features, the model integrating optimum wavelengths with GLGCM gave the highest classification rate of 93.14% and 90.91% for calibration and validation sets, respectively. Results indicated that the classification accuracy can be improved by combining spectral features with textural features and the fusion of critical spectral and textural features had better potential than single spectral extraction in classifying fresh and frozen-thawed pork meat. Copyright © 2014 Elsevier Ltd. All rights reserved.

Eigensolution analysis of spectral/hp continuous Galerkin approximations to advection-diffusion problems: Insights into spectral vanishing viscosity

NASA Astrophysics Data System (ADS)

Moura, R. C.; Sherwin, S. J.; Peiró, J.

2016-02-01

This study addresses linear dispersion-diffusion analysis for the spectral/hp continuous Galerkin (CG) formulation in one dimension. First, numerical dispersion and diffusion curves are obtained for the advection-diffusion problem and the role of multiple eigencurves peculiar to spectral/hp methods is discussed. From the eigencurves' behaviour, we observe that CG might feature potentially undesirable non-smooth dispersion/diffusion characteristics for under-resolved simulations of problems strongly dominated by either convection or diffusion. Subsequently, the linear advection equation augmented with spectral vanishing viscosity (SVV) is analysed. Dispersion and diffusion characteristics of CG with SVV-based stabilization are verified to display similar non-smooth features in flow regions where convection is much stronger than dissipation or vice-versa, owing to a dependency of the standard SVV operator on a local Péclet number. First a modification is proposed to the traditional SVV scaling that enforces a globally constant Péclet number so as to avoid the previous issues. In addition, a new SVV kernel function is suggested and shown to provide a more regular behaviour for the eigencurves along with a consistent increase in resolution power for higher-order discretizations, as measured by the extent of the wavenumber range where numerical errors are negligible. The dissipation characteristics of CG with the SVV modifications suggested are then verified to be broadly equivalent to those obtained through upwinding in the discontinuous Galerkin (DG) scheme. Nevertheless, for the kernel function proposed, the full upwind DG scheme is found to have a slightly higher resolution power for the same dissipation levels. These results show that improved CG-SVV characteristics can be pursued via different kernel functions with the aid of optimization algorithms.

Single cell analysis using surface enhanced Raman scattering (SERS) tags

PubMed Central

Nolan, John P.; Duggan, Erika; Liu, Er; Condello, Danilo; Dave, Isha; Stoner, Samuel A.

2013-01-01

Fluorescence is a mainstay of bioanalytical methods, offering sensitive and quantitative reporting, often in multiplexed or multiparameter assays. Perhaps the best example of the latter is flow cytometry, where instruments equipped with multiple lasers and detectors allow measurement of 15 or more different fluorophores simultaneously, but increases beyond this number are limited by the relatively broad emission spectra. Surface enhanced Raman scattering (SERS) from metal nanoparticles can produce signal intensities that rival fluorescence, but with narrower spectral features that allow a greater degree of multiplexing. We are developing nanoparticle SERS tags as well as Raman flow cytometers for multiparameter single cell analysis of suspension or adherent cells. SERS tags are based on plasmonically active nanoparticles (gold nanorods) whose plasmon resonance can be tuned to give optimal SERS signals at a desired excitation wavelength. Raman resonant compounds are adsorbed on the nanoparticles to confer a unique spectral fingerprint on each SERS tag, which are then encapsulated in a polymer coating for conjugation to antibodies or other targeting molecules. Raman flow cytometry employs a high resolution spectral flow cytometer capable of measuring the complete SERS spectra, as well as conventional flow cytometry measurements, from thousands of individual cells per minute. Automated spectral unmixing algorithms extract the contributions of each SERS tag from each cell to generate high content, multiparameter single cell population data. SERS-based cytometry is a powerful complement to conventional fluorescence-based cytometry. The narrow spectral features of the SERS signal enables more distinct probes to be measured in a smaller region of the optical spectrum with a single laser and detector, allowing for higher levels of multiplexing and multiparameter analysis. PMID:22498143

DOE Office of Scientific and Technical Information (OSTI.GOV)

Szymanski, J. J.; Brumby, Steven P.; Pope, P. A.

Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniquesmore » to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.« less

A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images

PubMed Central

Tang, Yunwei; Jing, Linhai; Ding, Haifeng

2017-01-01

The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA). Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods. PMID:29064416

[Research on spectra recognition method for cabbages and weeds based on PCA and SIMCA].

PubMed

Zu, Qin; Deng, Wei; Wang, Xiu; Zhao, Chun-Jiang

2013-10-01

In order to improve the accuracy and efficiency of weed identification, the difference of spectral reflectance was employed to distinguish between crops and weeds. Firstly, the different combinations of Savitzky-Golay (SG) convolutional derivation and multiplicative scattering correction (MSC) method were applied to preprocess the raw spectral data. Then the clustering analysis of various types of plants was completed by using principal component analysis (PCA) method, and the feature wavelengths which were sensitive for classifying various types of plants were extracted according to the corresponding loading plots of the optimal principal components in PCA results. Finally, setting the feature wavelengths as the input variables, the soft independent modeling of class analogy (SIMCA) classification method was used to identify the various types of plants. The experimental results of classifying cabbages and weeds showed that on the basis of the optimal pretreatment by a synthetic application of MSC and SG convolutional derivation with SG's parameters set as 1rd order derivation, 3th degree polynomial and 51 smoothing points, 23 feature wavelengths were extracted in accordance with the top three principal components in PCA results. When SIMCA method was used for classification while the previously selected 23 feature wavelengths were set as the input variables, the classification rates of the modeling set and the prediction set were respectively up to 98.6% and 100%.

Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.

A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expectedmore » clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.« less

A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching

PubMed Central

Mei, Xiaoguang; Ma, Yong; Li, Chang; Fan, Fan; Huang, Jun; Ma, Jiayi

2015-01-01

The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise. PMID:26205263

Network flexibility of the IRIDIUM (R) Global Mobile Satellite System

NASA Technical Reports Server (NTRS)

Hutcheson, Jonathan; Laurin, Mala

1995-01-01

The IRIDIUM system is a global personal communications system supported by a constellation of 66 low earth orbit (LEO) satellites and a collection of earth-based 'gateway' switching installations. Like traditional wireless cellular systems, coverage is achieved by a grid of cells in which bandwidth is reused for spectral efficiency. Unlike any cellular system ever built, the moving cells can be shared by multiple switching facilities. Noteworthy features of the IRIDIUM system include inter-satellite links, a GSM-based telephony architecture, and a geographically controlled system access process. These features, working in concert, permit flexible and reliable administration of the worldwide service area by gateway operators. This paper will explore this unique concept.

Anomalous photoluminescence in InP1−xBix

PubMed Central

Wu, Xiaoyan; Chen, Xiren; Pan, Wenwu; Wang, Peng; Zhang, Liyao; Li, Yaoyao; Wang, Hailong; Wang, Kai; Shao, Jun; Wang, Shumin

2016-01-01

Low temperature photoluminescence (PL) from InP1−xBix thin films with Bi concentrations in the 0–2.49% range reveals anomalous spectral features with strong and very broad (linewidth of 700 nm) PL signals compared to other bismide alloys. Multiple transitions are observed and their energy levels are found much smaller than the band-gap measured from absorption measurements. These transitions are related to deep levels confirmed by deep level transient spectroscopy, which effectively trap free holes and enhance radiative recombination. The broad luminescence feature is beneficial for making super-luminescence diodes, which can theoretically enhance spatial resolution beyond 1 μm in optical coherent tomography (OCT). PMID:27291823

The spectral energy distribution of the scattered light from dark clouds

NASA Technical Reports Server (NTRS)

Mattila, Kalevi; Schnur, G. F. O.

1989-01-01

A dark cloud is exposed to the ambient radiation field of integrated starlight in the Galaxy. Scattering of starlight by the dust particles gives rise to a diffuse surface brightness of the dark nebula. The intensity and the spectrum of this diffuse radiation can be used to investigate, e.g., the scattering parameters of the dust, the optical thickness of the cloud, and as a probe of the ambient radiation field at the location of the cloud. An understanding of the scattering process is also a prerequisite for the isolation of broad spectral features due to fluorescence or to any other non-scattering origin of the diffuse light. Model calculations are presented for multiple scattering in a spherical cloud. These calculations show that the different spectral shapes of the observed diffuse light can be reproduced with standard dust parameters. The possibility to use the observed spectrum as a diagnostic tool for analyzing the thickness of the cloud and the dust particle is discussed.

Constraints on the Compositions of Phobos and Deimos from Mineral Absorptions

NASA Technical Reports Server (NTRS)

Fraeman, A. A.; Murchie, S. L.; Arvidson, R. E.; Rivkin, A. S.; Morris, R. V.

2013-01-01

The compositions of Phobos and Deimos have remained controversial despite multiple Earth- and space-based observations acquired during the last 40 years. Phobos is composed of at least two spectral units that are both dark yet distinct at visible to near infrared wavelenghts; a spectrally red-sloped "red" unit covers most of the moon and a less red-sloped "blue" unit is present in the ejecta of the approximately 9-km diameter impact crater Stickney [1,2]. Deimos is similar spectrally to Phobos' "red" unit [2]. Here we report results from mapping mineral absorptions on Phobos and Deimos using visible/near infrared observations from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). We find evidence for an absorption feature at 0.65 m in the Phobos red unit and Deimos that is reproducible in observations from other instruments. The phase responsible is uncertain but may be a Fe-bearing phyllosilicate and/or graphite, consistent with the notion that Phobos and Deimos have compositions similar to CM carbonaceous chondrites [3].

Fiber-Optic Terahertz Data-Communication Networks

NASA Technical Reports Server (NTRS)

Chua, Peter L.; Lambert, James L.; Morookian, John M.; Bergman, Larry A.

1994-01-01

Network protocols implemented in optical domain. Fiber-optic data-communication networks utilize fully available bandwidth of single-mode optical fibers. Two key features of method: use of subpicosecond laser pulses as carrier signals and spectral phase modulation of pulses for optical implementation of code-division multiple access as multiplexing network protocol. Local-area network designed according to concept offers full crossbar functionality, security of data in transit through network, and capacity about 100 times that of typical fiber-optic local-area network in current use.

Multiplier, moderator, and reflector materials for lithium-vanadium fusion blankets.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gohar, Y.; Smith, D. L.

1999-10-07

The self-cooled lithium-vanadium fusion blanket concept has several attractive operational and environmental features. In this concept, liquid lithium works as the tritium breeder and coolant to alleviate issues of coolant breeder compatibility and reactivity. Vanadium alloy (V-4Cr-4Ti) is used as the structural material because of its superior performance relative to other alloys for this application. However, this concept has poor attenuation characteristics and energy multiplication for the DT neutrons. An advanced self-cooled lithium-vanadium fusion blanket concept has been developed to eliminate these drawbacks while maintaining all the attractive features of the conventional concept. An electrical insulator coating for the coolantmore » channels, spectral shifter (multiplier, and moderator) and reflector were utilized in the blanket design to enhance the blanket performance. In addition, the blanket was designed to have the capability to operate at high loading conditions of 2 MW/m{sup 2} surface heat flux and 10 MW/m{sup 2} neutron wall loading. This paper assesses the spectral shifter and the reflector materials and it defines the technological requirements of this advanced blanket concept.« less

Multiplier, moderator, and reflector materials for advanced lithium?vanadium fusion blankets

NASA Astrophysics Data System (ADS)

Gohar, Y.; Smith, D. L.

2000-12-01

The self-cooled lithium-vanadium fusion blanket concept has several attractive operational and environmental features. In this concept, liquid lithium works as the tritium breeder and coolant to alleviate issues of coolant breeder compatibility and reactivity. Vanadium alloy (V-4Cr-4Ti) is used as the structural material because of its superior performance relative to other alloys for this application. However, this concept has poor attenuation characteristics and energy multiplication for the DT neutrons. An advanced self-cooled lithium-vanadium fusion blanket concept has been developed to eliminate these drawbacks while maintaining all the attractive features of the conventional concept. An electrical insulator coating for the coolant channels, spectral shifter (multiplier, and moderator) and reflector were utilized in the blanket design to enhance the blanket performance. In addition, the blanket was designed to have the capability to operate at average loading conditions of 2 MW/m 2 surface heat flux and 10 MW/m 2 neutron wall loading. This paper assesses the spectral shifter and the reflector materials and it defines the technological requirements of this advanced blanket concept.

Laboratory Reflectance Spectra in the Middle-infrared: Effects of Grain Size on Spectral Features

NASA Astrophysics Data System (ADS)

Le Bras, A.; Erard, S.; Fulchignoni, M.

2000-10-01

Since spectral mineral features are sensitive to surface parameters, interpretation of remote-sensing asteroids spectra in terms of mineral composition is not easy nor unique, and laboratory spectra are needed in order to understand the influence of each parameter. We developped an experimental program at IAS, using the 2.5-120 microns interferometer spectrometer, to study the influence of surface parameters on mineral features. We present here the results obtained variing the grain size. We studied grain size effects with two types of terrestrial rocks: anorthosite (bright) and basalte (dark) in the 2-40 microns range. We observed variations of the spectral contrast with grain size, shifts in wavelengths and variations of the intensity of some characteristic spectral features, and appearence of transparency features at wavelengths longer than 8 microns.

Laboratory Thermal Infrared and Visible to Near-Infrared Spectral Analysis of Chert

NASA Astrophysics Data System (ADS)

McDowell, M. L.; Hamilton, V. E.

2007-12-01

Though basaltic materials dominate the composition of the Martian surface, a material with a relatively high silica component in an area of Eos Chasma was reported by [1] from thermal infrared (TIR) data. The spectrum of the silica phase resembles quartz or chert, but with the existing information it is difficult to tell which phase best fits the observations. Though quartz, chert, and amorphous silica are chemically identical (SiO2), their physical differences (e.g., microstructures) result in different TIR spectral characteristics. Previous studies have analyzed a limited number of chert samples using emission infrared spectroscopy [2] and transmission infrared spectroscopy [3]. We continue these preliminary studies with an investigation aiming to more completely understand and document the variation in spectral character of cherts. This knowledge may help to identify the silica phase in Eos Chasma and any future discoveries. Our study includes a more extensive sampling of geologic chert in hand sample (>15 samples) with various sources, methods of formation, surface textures, and crystallinities. We analyzed their visible to near-infrared (VNIR) reflectance spectra, as well as spectral features in TIR emission spectra. We measured multiple locations on each sample to determine spectral homogeneity across the sample and between various orientations. Where possible, natural, cut, and recently fractured surfaces were measured. We compared the collected TIR spectra for similarities and differences in shape and spectral contrast within each sample and between samples that may relate to variations in the samples' structure (e.g. crystallinity, and surface texture). VNIR measurements show features indicative of non-silica phases and water that may be present in the cherts. [1] Hamilton, V.E. (2005) Eos Trans. AGU, Fall Meeting Suppl., Abstract P24A-08. [2] Michalski, J.R. (2005) PhD Diss., ASU, Tempe. [3] Long, D. G. et al. (2001) Canadian Archaeological Assoc., 33rd Meeting.

Nonlinear acoustic spectroscopy of cracked flaws and disbonds: Fundamentals, techniques, and applications

NASA Astrophysics Data System (ADS)

Maev, R. Gr.; Solodov, I. Yu.

2000-05-01

Classical nonlinear acoustics of solids operates with distributed material nonlinearity related to unharmonicity of molecular interaction forces. Weakening of molecular bonds in a defect area or intermittent lack of elastic coupling between the faces of a vibrating crack or unbond ("clapping") results in anomalously high local contact acoustic nonlinearity (CAN). CAN properties and spectral features are different from those of the classical analog and important to develop new acoustic NDE techniques. Three approaches to nonlinear NDE methodology have been experimentally verified: low-frequency (hundreds of Hz) vibration technique, intermediate-frequency (hundreds of kHz) standing wave and high-frequency (tens of MHz) propagation modes. Low-frequency nonlinear contact vibrations revealed multiple sub- and super-harmonics generation featuring non-monotonous (sinx/x type) spectra. Parametric instability observed in resonator with a nonlinear contact leads to the output spectrum splitting up into successive sub-harmonics as the wave amplitude increases. High-frequency experiments demonstrated abnormal increases in the third harmonic amplitude: 3 or 4 order enhancement of the 3-ω nonlinear parameter was measured for the nonlinear contact. The CAN spectral features in both acoustic and vibration modes were used for nonlinear NDE of simulated and realistic flaws in glass, metal welds, etc. The sensitivities of the techniques are compared and their practical applicability assessed.

Airborne spectroradiometry: The application of AIS data to detecting subtle mineral absorption features

NASA Technical Reports Server (NTRS)

Cocks, T. D.; Green, A. A.

1986-01-01

Analysis of Airborne Imaging Spectrometer (AIS) data acquired in Australia has revealed a number of operational problems. Horizontal striping in AIS imagery and spectral distortions due to order overlap were investigated. Horizontal striping, caused by grating position errors can be removed with little or no effect on spectral details. Order overlap remains a problem that seriously compromises identification of subtle mineral absorption features within AIS spectra. A spectrometric model of the AIS was developed to assist in identifying spurious spectral features, and will be used in efforts to restore the spectral integrity of the data.

An integrated condition-monitoring method for a milling process using reduced decomposition features

NASA Astrophysics Data System (ADS)

Liu, Jie; Wu, Bo; Wang, Yan; Hu, Youmin

2017-08-01

Complex and non-stationary cutting chatter affects productivity and quality in the milling process. Developing an effective condition-monitoring approach is critical to accurately identify cutting chatter. In this paper, an integrated condition-monitoring method is proposed, where reduced features are used to efficiently recognize and classify machine states in the milling process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition, and Shannon power spectral entropy is calculated to extract features from the decomposed signals. Principal component analysis is adopted to reduce feature size and computational cost. With the extracted feature information, the probabilistic neural network model is used to recognize and classify the machine states, including stable, transition, and chatter states. Experimental studies are conducted, and results show that the proposed method can effectively detect cutting chatter during different milling operation conditions. This monitoring method is also efficient enough to satisfy fast machine state recognition and classification.

Multiple populations within globular clusters in Early-type galaxies Exploring their effect on stellar initial mass function estimates

NASA Astrophysics Data System (ADS)

Chantereau, W.; Usher, C.; Bastian, N.

2018-05-01

It is now well-established that most (if not all) ancient globular clusters host multiple populations, that are characterised by distinct chemical features such as helium abundance variations along with N-C and Na-O anti-correlations, at fixed [Fe/H]. These very distinct chemical features are similar to what is found in the centres of the massive early-type galaxies and may influence measurements of the global properties of the galaxies. Additionally, recent results have suggested that M/L variations found in the centres of massive early-type galaxies might be due to a bottom-heavy stellar initial mass function. We present an analysis of the effects of globular cluster-like multiple populations on the integrated properties of early-type galaxies. In particular, we focus on spectral features in the integrated optical spectrum and the global mass-to-light ratio that have been used to infer variations in the stellar initial mass function. To achieve this we develop appropriate stellar population synthesis models and take into account, for the first time, an initial-final mass relation which takes into consideration a varying He abundance. We conclude that while the multiple populations may be present in massive early-type galaxies, they are likely not responsible for the observed variations in the mass-to-light ratio and IMF sensitive line strengths. Finally, we estimate the fraction of stars with multiple populations chemistry that come from disrupted globular clusters within massive ellipticals and find that they may explain some of the observed chemical patterns in the centres of these galaxies.

Changes in the Far UV Spectrum of Eta Carinae Near the 2003 Minimum

NASA Technical Reports Server (NTRS)

Iping, R. C.; Gull, T. R.; Sonneborn, G.; Massa, D.; Vieira, G. L.; Nielsen, K. E.

2004-01-01

High resolution 905-1180 spectra of \\eta Carinae have been obtained with the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite at nine epochs between February 2000 and June 2003 . This period of time extends from the broad maximum up to the very beginning of the minimum of the 5.52-year period initially discovered by A. Damineli. The flux levels were unchanged between February 2000 through February 2003 with minor spectral differences. The X-Ray minimum started on June 29, 2003 . Three observations were accomplished on June 10, June 17 and June 27 leading up to the minimum. Substantial changes were present in the June 10 and June 17 spectra, but a very significant change occurred by June 27, 2003. Longward of 1100A, the overall flux dropped 10 to 30 %. Shortward of 1100A, there are spectral intervals with NO decrease in flux even down to the shortest wavelengths (920--950 ). This indicates that dust absorption has a negligible role in the observed spectral changes and that line absorptions play a major role. Throughout the spectrum there are intervals ranging in width of 3-10A with strong increased absorption. Significant absorptions may be associated with the red portion of the following stellar wind lines: C III 977, O VI 1031,1037, P V 1117, while other absorption features are much broader, more extended and not clearly associated with well-known spectral transitions. Given the complexity of the STIS echelle spectra taken in this period of time, many of these absorption features are likely due to multiple absorption lines

Nonphotosynthetic Pigments as Potential Biosignatures

PubMed Central

Cockell, Charles S.; Meadows, Victoria S.

2015-01-01

Abstract Previous work on possible surface reflectance biosignatures for Earth-like planets has typically focused on analogues to spectral features produced by photosynthetic organisms on Earth, such as the vegetation red edge. Although oxygenic photosynthesis, facilitated by pigments evolved to capture photons, is the dominant metabolism on our planet, pigmentation has evolved for multiple purposes to adapt organisms to their environment. We present an interdisciplinary study of the diversity and detectability of nonphotosynthetic pigments as biosignatures, which includes a description of environments that host nonphotosynthetic biologically pigmented surfaces, and a lab-based experimental analysis of the spectral and broadband color diversity of pigmented organisms on Earth. We test the utility of broadband color to distinguish between Earth-like planets with significant coverage of nonphotosynthetic pigments and those with photosynthetic or nonbiological surfaces, using both 1-D and 3-D spectral models. We demonstrate that, given sufficient surface coverage, nonphotosynthetic pigments could significantly impact the disk-averaged spectrum of a planet. However, we find that due to the possible diversity of organisms and environments, and the confounding effects of the atmosphere and clouds, determination of substantial coverage by biologically produced pigments would be difficult with broadband colors alone and would likely require spectrally resolved data. Key Words: Biosignatures—Exoplanets—Halophiles—Pigmentation—Reflectance spectroscopy—Spectral models. Astrobiology 15, 341–361. PMID:25941875

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Location of γ -ray emission and magnetic field strengths in OJ 287

DOE PAGES

Hodgson, J. A.; Krichbaum, T. P.; Marscher, A. P.; ...

2017-01-06

We report the γ-ray BL Lac object OJ 287 is known to exhibit inner-parsec “jet-wobbling”, high degrees of variability at all wavelengths and quasi-stationary features, including an apparent (≈100°) position-angle change in projection on the sky plane. Sub-50 micro-arcsecond resolution 86 GHz observations with the global mm-VLBI array (GMVA) supplement ongoing multi-frequency VLBI blazar monitoring at lower frequencies. Using these maps, together with cm/mm total intensity and γ-ray observations from Fermi-LAT from 2008-2014, we aim to Observations with the GMVA offer approximately double the angular resolution compared with 43 GHz VLBA observations and enable us to observe above the synchrotronmore » self-absorption peak frequency. Fermi-LAT γ-ray data were reduced and analysed. The jet was spectrally decomposed at multiple locations along the jet. From this, we could derive estimates of the magnetic field using equipartition and synchrotron self-absorption arguments. How the field decreases down the jet provided an estimate of the distance to the jet apex and an estimate of the magnetic field strength at the jet apex and in the broad line region. Combined with accurate kinematics, we attempt to locate the site of γ-ray activity, radio flares, and spectral changes. Strong γ-ray flares appeared to originate from either the so-called core region, a downstream stationary feature, or both, with γ-ray activity significantly correlated with radio flaring in the downstream quasi-stationary feature. Magnetic field estimates were determined at multiple locations along the jet, with the magnetic field found to be ≥1.6 G in the core and ≤0.4 G in the downstream quasi-stationary feature. Finally, we therefore found upper limits on the location of the VLBI core as ≲6.0 pc from the jet apex and determined an upper limit on the magnetic field near the jet base of the order of thousands of Gauss.« less

Location of γ -ray emission and magnetic field strengths in OJ 287

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodgson, J. A.; Krichbaum, T. P.; Marscher, A. P.

We report the γ-ray BL Lac object OJ 287 is known to exhibit inner-parsec “jet-wobbling”, high degrees of variability at all wavelengths and quasi-stationary features, including an apparent (≈100°) position-angle change in projection on the sky plane. Sub-50 micro-arcsecond resolution 86 GHz observations with the global mm-VLBI array (GMVA) supplement ongoing multi-frequency VLBI blazar monitoring at lower frequencies. Using these maps, together with cm/mm total intensity and γ-ray observations from Fermi-LAT from 2008-2014, we aim to Observations with the GMVA offer approximately double the angular resolution compared with 43 GHz VLBA observations and enable us to observe above the synchrotronmore » self-absorption peak frequency. Fermi-LAT γ-ray data were reduced and analysed. The jet was spectrally decomposed at multiple locations along the jet. From this, we could derive estimates of the magnetic field using equipartition and synchrotron self-absorption arguments. How the field decreases down the jet provided an estimate of the distance to the jet apex and an estimate of the magnetic field strength at the jet apex and in the broad line region. Combined with accurate kinematics, we attempt to locate the site of γ-ray activity, radio flares, and spectral changes. Strong γ-ray flares appeared to originate from either the so-called core region, a downstream stationary feature, or both, with γ-ray activity significantly correlated with radio flaring in the downstream quasi-stationary feature. Magnetic field estimates were determined at multiple locations along the jet, with the magnetic field found to be ≥1.6 G in the core and ≤0.4 G in the downstream quasi-stationary feature. Finally, we therefore found upper limits on the location of the VLBI core as ≲6.0 pc from the jet apex and determined an upper limit on the magnetic field near the jet base of the order of thousands of Gauss.« less

Forest tree species clssification based on airborne hyper-spectral imagery

NASA Astrophysics Data System (ADS)

Dian, Yuanyong; Li, Zengyuan; Pang, Yong

2013-10-01

Forest precision classification products were the basic data for surveying of forest resource, updating forest subplot information, logging and design of forest. However, due to the diversity of stand structure, complexity of the forest growth environment, it's difficult to discriminate forest tree species using multi-spectral image. The airborne hyperspectral images can achieve the high spatial and spectral resolution imagery of forest canopy, so it will good for tree species level classification. The aim of this paper was to test the effective of combining spatial and spectral features in airborne hyper-spectral image classification. The CASI hyper spectral image data were acquired from Liangshui natural reserves area. Firstly, we use the MNF (minimum noise fraction) transform method for to reduce the hyperspectral image dimensionality and highlighting variation. And secondly, we use the grey level co-occurrence matrix (GLCM) to extract the texture features of forest tree canopy from the hyper-spectral image, and thirdly we fused the texture and the spectral features of forest canopy to classify the trees species using support vector machine (SVM) with different kernel functions. The results showed that when using the SVM classifier, MNF and texture-based features combined with linear kernel function can achieve the best overall accuracy which was 85.92%. It was also confirm that combine the spatial and spectral information can improve the accuracy of tree species classification.

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

NASA Technical Reports Server (NTRS)

Solarna, David; Moser, Gabriele; Le Moigne-Stewart, Jacqueline; Serpico, Sebastiano B.

2017-01-01

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Separation of detector non-linearity issues and multiple ionization satellites in alpha-particle PIXE

NASA Astrophysics Data System (ADS)

Campbell, John L.; Ganly, Brianna; Heirwegh, Christopher M.; Maxwell, John A.

2018-01-01

Multiple ionization satellites are prominent features in X-ray spectra induced by MeV energy alpha particles. It follows that the accuracy of PIXE analysis using alpha particles can be improved if these features are explicitly incorporated in the peak model description when fitting the spectra with GUPIX or other codes for least-squares fitting PIXE spectra and extracting element concentrations. A method for this incorporation is described and is tested using spectra recorded on Mars by the Curiosity rover's alpha particle X-ray spectrometer. These spectra are induced by both PIXE and X-ray fluorescence, resulting in a spectral energy range from ∼1 to ∼25 keV. This range is valuable in determining the energy-channel calibration, which departs from linearity at low X-ray energies. It makes it possible to separate the effects of the satellites from an instrumental non-linearity component. The quality of least-squares spectrum fits is significantly improved, raising the level of confidence in analytical results from alpha-induced PIXE.

Raman spectroscopy fingerprint of stainless steel-MWCNTs nanocomposite processed by ball-milling

NASA Astrophysics Data System (ADS)

dos Reis, Marcos Allan Leite; Barbosa Neto, Newton Martins; de Sousa, Mário Edson Santos; Araujo, Paulo T.; Simões, Sónia; Vieira, Manuel F.; Viana, Filomena; Loayza, Cristhian R. L.; Borges, Diego J. A.; Cardoso, Danyella C. S.; Assunção, Paulo D. C.; Braga, Eduardo M.

2018-01-01

Stainless steel 304L alloy powder and multiwalled carbon nanotubes were mixed by ball-milling under ambient atmosphere and in a broad range of milling times, which spans from 0 to 120 min. Here, we provided spectroscopic signatures for several distinct composites produced, to show that the Raman spectra present interesting splittings of the D-band feature into two main sub-bands, D-left and D-right, together with several other secondary features. The G-band feature also presents multiple splittings that are related to the outer and inner diameter distributions intrinsic to the multiwalled carbon nanotube samples. A discussion about the second order 2D-band (also known as G'-band) is also provided. The results reveal that the multiple spectral features observed in the D-band are related to an increased chemical functionalization. A lower content of amorphous carbon at 60 and 90 min of milling time is verified and the G-band frequencies associated to the tubes in the outer diameters distribution is upshifted, which suggests that doping induced by strain is taking place in the milled samples. The results indicate that Raman spectroscopy can be a powerful tool for a fast and non-destructive characterization of carbon nanocomposites used in powder metallurgy manufacturing processes.

Spectral feature measurements and analyses of the East Lake

NASA Astrophysics Data System (ADS)

Fang, Shenghui; Zhou, Yuan; Zhu, Wu

2005-10-01

It is one of basis of water color remote sensing to investigate the method to obtain and analyze the spectral features of the water bodies. This paper concerns the above-water method for the spectral measurements of inland water. A series of experiments were taken in areas of the East Lake with the EPP2000CCD radiometer, and the geometry attitude of the observation and the method of the elimination of the noise of the water Signals will be discussed. The method of the above-water spectral measurements was studied from the point of view of error source. On the basis of the experiments of the water depth and the observing direction form the sun and surface, it is suggested to remove the radiances of the whitecaps, surface-reflected sun glint and skylight which have not the spectral features of water from the lake surface by specialized observing attitude and data processing. At last, a suit of methods is concluded for the water body of the East Lake in measuring and analyzing the spectral features from above-water.

Detecting photovoltaic solar panels using hyperspectral imagery and estimating solar power production

NASA Astrophysics Data System (ADS)

Czirjak, Daniel

2017-04-01

Remote sensing platforms have consistently demonstrated the ability to detect, and in some cases identify, specific targets of interest, and photovoltaic solar panels are shown to have a unique spectral signature that is consistent across multiple manufacturers and construction methods. Solar panels are proven to be detectable in hyperspectral imagery using common statistical target detection methods such as the adaptive cosine estimator, and false alarms can be mitigated through the use of a spectral verification process that eliminates pixels that do not have the key spectral features of photovoltaic solar panel reflectance spectrum. The normalized solar panel index is described and is a key component in the false-alarm mitigation process. After spectral verification, these solar panel arrays are confirmed on openly available literal imagery and can be measured using numerous open-source algorithms and tools. The measurements allow for the assessment of overall solar power generation capacity using an equation that accounts for solar insolation, the area of solar panels, and the efficiency of the solar panels conversion of solar energy to power. Using a known location with readily available information, the methods outlined in this paper estimate the power generation capabilities within 6% of the rated power.

Classification of visible and infrared hyperspectral images based on image segmentation and edge-preserving filtering

NASA Astrophysics Data System (ADS)

Cui, Binge; Ma, Xiudan; Xie, Xiaoyun; Ren, Guangbo; Ma, Yi

2017-03-01

The classification of hyperspectral images with a few labeled samples is a major challenge which is difficult to meet unless some spatial characteristics can be exploited. In this study, we proposed a novel spectral-spatial hyperspectral image classification method that exploited spatial autocorrelation of hyperspectral images. First, image segmentation is performed on the hyperspectral image to assign each pixel to a homogeneous region. Second, the visible and infrared bands of hyperspectral image are partitioned into multiple subsets of adjacent bands, and each subset is merged into one band. Recursive edge-preserving filtering is performed on each merged band which utilizes the spectral information of neighborhood pixels. Third, the resulting spectral and spatial feature band set is classified using the SVM classifier. Finally, bilateral filtering is performed to remove "salt-and-pepper" noise in the classification result. To preserve the spatial structure of hyperspectral image, edge-preserving filtering is applied independently before and after the classification process. Experimental results on different hyperspectral images prove that the proposed spectral-spatial classification approach is robust and offers more classification accuracy than state-of-the-art methods when the number of labeled samples is small.

Generalization of the Lyot filter and its application to snapshot spectral imaging.

PubMed

Gorman, Alistair; Fletcher-Holmes, David William; Harvey, Andrew Robert

2010-03-15

A snapshot multi-spectral imaging technique is described which employs multiple cascaded birefringent interferometers to simultaneously spectrally filter and demultiplex multiple spectral images onto a single detector array. Spectral images are recorded directly without the need for inversion and without rejection of light and so the technique offers the potential for high signal-to-noise ratio. An example of an eight-band multi-spectral movie sequence is presented; we believe this is the first such demonstration of a technique able to record multi-spectral movie sequences without the need for computer reconstruction.

Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors.

PubMed

Jang, Woo-Yong; Hayat, Majeed M; Godoy, Sebastián E; Bender, Steven C; Zarkesh-Ha, Payman; Krishna, Sanjay

2011-09-26

While quantum dots-in-a-well (DWELL) infrared photodetectors have the feature that their spectral responses can be shifted continuously by varying the applied bias, the width of the spectral response at any applied bias is not sufficiently narrow for use in multispectral sensing without the aid of spectral filters. To achieve higher spectral resolutions without using physical spectral filters, algorithms have been developed for post-processing the DWELL's bias-dependent photocurrents resulting from probing an object of interest repeatedly over a wide range of applied biases. At the heart of these algorithms is the ability to approximate an arbitrary spectral filter, which we desire the DWELL-algorithm combination to mimic, by forming a weighted superposition of the DWELL's non-orthogonal spectral responses over a range of applied biases. However, these algorithms assume availability of abundant DWELL data over a large number of applied biases (>30), leading to large overall acquisition times in proportion with the number of biases. This paper reports a new multispectral sensing algorithm to substantially compress the number of necessary bias values subject to a prescribed performance level across multiple sensing applications. The algorithm identifies a minimal set of biases to be used in sensing only the relevant spectral information for remote-sensing applications of interest. Experimental results on target spectrometry and classification demonstrate a reduction in the number of required biases by a factor of 7 (e.g., from 30 to 4). The tradeoff between performance and bias compression is thoroughly investigated. © 2011 Optical Society of America

VizieR Online Data Catalog: Berkeley supernova Ia program. II. (Silverman+, 2012)

NASA Astrophysics Data System (ADS)

Silverman, J. M.; Kong, J. J.; Filippenko, A. V.

2013-08-01

In this second paper in a series, we present measurements of spectral features of 432 low-redshift (z<0.1) optical spectra of 261 Type Ia supernovae (SNe Ia) within 20d of maximum brightness. The data were obtained from 1989 to the end of 2008 as part of the Berkeley Supernova Ia Program (BSNIP) and are presented in BSNIP I by Silverman et al. (J/MNRAS/425/1789). We describe in detail our method of automated, robust spectral feature definition and measurement which expands upon similar previous studies. Using this procedure, we attempt to measure expansion velocities, pseudo-equivalent widths (pEWs), spectral feature depths and fluxes at the centre and endpoints of each of nine major spectral feature complexes. (10 data files).

M3 spectral analysis of lunar swirls and the link between optical maturation and surface hydroxyl formation at magnetic anomalies

USGS Publications Warehouse

Kramer, G.Y.; Besse, S.; Dhingra, D.; Nettles, J.; Klima, R.; Garrick-Bethell, I.; Clark, Roger N.; Combe, J.-P.; Head, J. W.; Taylor, L.A.; Pieters, C.M.; Boardman, J.; McCord, T.B.

2011-01-01

We examined the lunar swirls using data from the Moon Mineralogy Mapper (M3). The improved spectral and spatial resolution of M3 over previous spectral imaging data facilitates distinction of subtle spectral differences, and provides new information about the nature of these enigmatic features. We characterized spectral features of the swirls, interswirl regions (dark lanes), and surrounding terrain for each of three focus regions: Reiner Gamma, Gerasimovich, and Mare Ingenii. We used Principle Component Analysis to identify spectrally distinct surfaces at each focus region, and characterize the spectral features that distinguish them. We compared spectra from small, recent impact craters with the mature soils into which they penetrated to examine differences in maturation trends on- and off-swirl. Fresh, on-swirl crater spectra are higher albedo, exhibit a wider range in albedos and have well-preserved mafic absorption features compared with fresh off-swirl craters. Albedoand mafic absorptions are still evident in undisturbed, on-swirl surface soils, suggesting the maturation process is retarded. The spectral continuum is more concave compared with off-swirl spectra; a result of the limited spectral reddening being mostly constrained to wavelengths less than ∼1500 nm. Off-swirl spectra show very little reddening or change in continuum shape across the entire M3 spectral range. Off-swirl spectra are dark, have attenuated absorption features, and the narrow range in off-swirl albedos suggests off-swirl regions mature rapidly. Spectral parameter maps depicting the relative OH surface abundance for each of our three swirl focus regions were created using the depth of the hydroxyl absorption feature at 2.82 μm. For each of the studied regions, the 2.82 μm absorption feature is significantly weaker on-swirl than off-swirl, indicating the swirls are depleted in OH relative to their surroundings. The spectral characteristics of the swirls and adjacent terrains from all three focus regions support the hypothesis that the magnetic anomalies deflect solar wind ions away from the swirls and onto off-swirl surfaces. Nanophase iron (npFe0) is largely responsible for the spectral characteristics we attribute to space weathering and maturation, and is created by vaporization/deposition by micrometeorite impacts and sputtering/reduction by solar wind ions. On the swirls, the decreased proton flux slows the spectral effects of space weathering (relative to nonswirl regions) by limiting the npFe0 production mechanism almost exclusively to micrometeoroid impact vaporization/deposition. Immediately adjacent to the swirls, maturation is accelerated by the increased flux of protons deflected from the swirls.

Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture.

Detection of Chorus Elements and other Wave Signatures Using Geometric Computational Techniques in the Van Allen radiation belts

NASA Astrophysics Data System (ADS)

Sengupta, A.; Kletzing, C.; Howk, R.; Kurth, W. S.

2017-12-01

An important goal of the Van Allen Probes mission is to understand wave particle interactions that can energize relativistic electron in the Earth's Van Allen radiation belts. The EMFISIS instrumentation suite provides measurements of wave electric and magnetic fields of wave features such as chorus that participate in these interactions. Geometric signal processing discovers structural relationships, e.g. connectivity across ridge-like features in chorus elements to reveal properties such as dominant angles of the element (frequency sweep rate) and integrated power along the a given chorus element. These techniques disambiguate these wave features against background hiss-like chorus. This enables autonomous discovery of chorus elements across the large volumes of EMFISIS data. At the scale of individual or overlapping chorus elements, topological pattern recognition techniques enable interpretation of chorus microstructure by discovering connectivity and other geometric features within the wave signature of a single chorus element or between overlapping chorus elements. Thus chorus wave features can be quantified and studied at multiple scales of spectral geometry using geometric signal processing techniques. We present recently developed computational techniques that exploit spectral geometry of chorus elements and whistlers to enable large-scale automated discovery, detection and statistical analysis of these events over EMFISIS data. Specifically, we present different case studies across a diverse portfolio of chorus elements and discuss the performance of our algorithms regarding precision of detection as well as interpretation of chorus microstructure. We also provide large-scale statistical analysis on the distribution of dominant sweep rates and other properties of the detected chorus elements.

Thermal Infrared Spectral Band Detection Limits for Unidentified Surface Materials

NASA Technical Reports Server (NTRS)

Kirkland, Laurel E.; Herr, Kenneth C.; Salisbury, John W.

2001-01-01

Infrared emission spectra recorded by airborne or satellite spectrometers can be searched for spectral features to determine the composition of rocks on planetary surfaces. Surface materials are identified by detections of characteristic spectral bands. We show how to define whether to accept an observed spectral feature as a detection when the target material is unknown. We also use remotely sensed spectra measured by the Thermal Emission Spectrometer (TES) and the Spatially Enhanced Broadband Array Spectrograph System to illustrate the importance of instrument parameters and surface properties on band detection limits and how the variation in signal-to-noise ratio with wavelength affects the bands that are most detectable for a given instrument. The spectrometer's sampling interval, spectral resolution, signal-to-noise ratio as a function of wavelength, and the sample's surface properties influence whether the instrument can detect a spectral feature exhibited by a material. As an example, in the 6-13 micrometer wavelength region, massive carbonates exhibit two bands: a very strong, broad feature at approximately 6.5 micrometers and a less intense, sharper band at approximately 11.25 micrometers. Although the 6.5-micrometer band is stronger and broader in laboratory-measured spectra, the 11.25-micrometer band will cause a more detectable feature in TES spectra.

Optical filter for highlighting spectral features part I: design and development of the filter for discrimination of human skin with and without an application of cosmetic foundation.

PubMed

Nishino, Ken; Nakamura, Mutsuko; Matsumoto, Masayuki; Tanno, Osamu; Nakauchi, Shigeki

2011-03-28

Light reflected from an object's surface contains much information about its physical and chemical properties. Changes in the physical properties of an object are barely detectable in spectra. Conventional trichromatic systems, on the other hand, cannot detect most spectral features because spectral information is compressively represented as trichromatic signals forming a three-dimensional subspace. We propose a method for designing a filter that optically modulates a camera's spectral sensitivity to find an alternative subspace highlighting an object's spectral features more effectively than the original trichromatic space. We designed and developed a filter that detects cosmetic foundations on human face. Results confirmed that the filter can visualize and nondestructively inspect the foundation distribution.

Heterodyne detection using spectral line pairing for spectral phase encoding optical code division multiple access and dynamic dispersion compensation.

PubMed

Yang, Yi; Foster, Mark; Khurgin, Jacob B; Cooper, A Brinton

2012-07-30

A novel coherent optical code-division multiple access (OCDMA) scheme is proposed that uses spectral line pairing to generate signals suitable for heterodyne decoding. Both signal and local reference are transmitted via a single optical fiber and a simple balanced receiver performs sourceless heterodyne detection, canceling speckle noise and multiple-access interference (MAI). To validate the idea, a 16 user fully loaded phase encoded system is simulated. Effects of fiber dispersion on system performance are studied as well. Both second and third order dispersion management is achieved by using a spectral phase encoder to adjust phase shifts of spectral components at the optical network unit (ONU).

The far-ultraviolet /1180-1950 A/ emission spectrum of Arcturus

NASA Technical Reports Server (NTRS)

Mckinney, W. R.; Giles, J. W.; Moos, H. W.

1976-01-01

The far-ultraviolet (1180-1950 A) emission spectrum of the K2 IIIp star, Arcturus, has been obtained with a rocket-borne multichannel spectrometer. The use of multiple detectors gave an increase in effective observing time and permitted an improvement in spectral resolution over two previous rocket measurements. H I at 1216-A and O I at 1304 A are the only identified emissions, and the observed H I 1216-A flux is low compared with previous observations. A third unidentified feature was observed at 1511 A. The absence of many lines found in emission from the sun is striking. The absence of certain features implies that the coronal temperature must be either below 50,000 K or above 350,000 K.

Labview Interface Concepts Used in NASA Scientific Investigations and Virtual Instruments

NASA Technical Reports Server (NTRS)

Roth, Don J.; Parker, Bradford H.; Rapchun, David A.; Jones, Hollis H.; Cao, Wei

2001-01-01

This article provides an overview of several software control applications developed for NASA using LabVIEW. The applications covered here include (1) an Ultrasonic Measurement System for nondestructive evaluation of advanced structural materials, an Xray Spectral Mapping System for characterizing the quality and uniformity of developing photon detector materials, (2) a Life Testing System for these same materials, (3) and the instrument panel for an aircraft mounted Cloud Absorption Radiometer that measures the light scattered by clouds in multiple spectral bands. Many of the software interface concepts employed are explained. Panel layout and block diagram (code) strategies for each application are described. In particular, some of the more unique features of the applications' interfaces and source code are highlighted. This article assumes that the reader has a beginner-to-intermediate understanding of LabVIEW methods.

Spectral feature design in high dimensional multispectral data

NASA Technical Reports Server (NTRS)

Chen, Chih-Chien Thomas; Landgrebe, David A.

1988-01-01

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Acute monocytic leukemia and multiple abnormalities in a child with duplication of 1q detected by GTG-banding and SKY.

PubMed

Scrideli, Carlos A; Baruffi, Marcelo R; Squire, Jeremy A; Ramos, Ester S; Karaskova, Jana; Heck, Benjamin; Tone, Luiz G

2005-12-01

Patients with 1q duplication have demonstrated a wide range of multiple congenital abnormalities. Alterations involving this chromosomal region have being described in hematopoietic malignancies and a series of candidate genes that may be associated with neoplasias have been mapped in this region. We describe a case of partial trisomy 1q "syndrome" and acute monocytic leukemia. Cytogenetic study of the bone marrow cells by GTG-banding and spectral karyotyping (SKY) showed dup(1)(q23q44) in all cells analyzed. The dismorphological features with the dup(1q) suggest a constitutional chromosome alteration and the first, in our knowledge, association of a trisomy 1q "syndrome" with AML.

Automatic classification of retinal three-dimensional optical coherence tomography images using principal component analysis network with composite kernels

NASA Astrophysics Data System (ADS)

Fang, Leyuan; Wang, Chong; Li, Shutao; Yan, Jun; Chen, Xiangdong; Rabbani, Hossein

2017-11-01

We present an automatic method, termed as the principal component analysis network with composite kernel (PCANet-CK), for the classification of three-dimensional (3-D) retinal optical coherence tomography (OCT) images. Specifically, the proposed PCANet-CK method first utilizes the PCANet to automatically learn features from each B-scan of the 3-D retinal OCT images. Then, multiple kernels are separately applied to a set of very important features of the B-scans and these kernels are fused together, which can jointly exploit the correlations among features of the 3-D OCT images. Finally, the fused (composite) kernel is incorporated into an extreme learning machine for the OCT image classification. We tested our proposed algorithm on two real 3-D spectral domain OCT (SD-OCT) datasets (of normal subjects and subjects with the macular edema and age-related macular degeneration), which demonstrated its effectiveness.

Remotely sensed detection of sulfates on Mars: Laboratory measurements and spacecraft observations

NASA Astrophysics Data System (ADS)

Cooper, Christopher David

Visible, near-infrared, and mid-infrared spectroscopic measurements were made of physically realistic analogs of Martian soil containing silicates and sulfates. These measurements indicate that the physical structure of soil will control its spectroscopic properties. Orbital measurements from the Thermal Emission Spectrometer (TES) identified features similar to those seen in the laboratory mixtures. Maps were made of this sulfate-cemented soil which indicated that the presence of this material is not geographically controlled and hints at an origin for duricrust in atmosphere-surface interactions. Further confirmation comes from combining data from TES and the Imaging Spectrometer for Mars (ISM). This data shows a congruence between sulfate spectral features and water features. The likely form of the mappable sulfate in Martian soils is therefore a cemented mixture of hydrated sulfate mixed with silicates and oxides derived from crustal rocks. The combination of ISM and TES spectra in particular and spectra from multiple wavelength regimes in general also is an excellent technique for addressing other problems of interest regarding the geology of Mars. A number of topics including rock coatings in Syrtis Major and the nature of low albedo rock assemblages are addressed. Syrtis Major is found to behave differently in the thermal and near infrared, likely indicating that the spectral features are not related to simple coatings but perhaps processes like penetrative oxidation. TES Type I rocks are found to be high in pyroxene, but TES Type II rocks do not have a correlation with pyroxene. Spectral mixing trends indicate that dust and rock are the dominant two variables in surface composition on a large scale. A smaller mixing trend involves the physical breakup of sulfate-cemented soils into a loose, fine-grained, but still hydrated form. In all, this work provides strong evidence for the global identification and distribution of sulfate minerals in the Martian soil.

Dual-wavelength quantum cascade laser for trace gas spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jágerská, J.; Tuzson, B.; Mangold, M.

2014-10-20

We demonstrate a sequentially operating dual-wavelength quantum cascade laser with electrically separated laser sections, emitting single-mode at 5.25 and 6.25 μm. Based on a single waveguide ridge, this laser represents a considerable asset to optical sensing and trace gas spectroscopy, as it allows probing multiple gas species with spectrally distant absorption features using conventional optical setups without any beam combining optics. The laser capability was demonstrated in simultaneous NO and NO{sub 2} detection, reaching sub-ppb detection limits and selectivity comparable to conventional high-end spectroscopic systems.

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

Annoyance from industrial noise: indicators for a wide variety of industrial sources.

PubMed

Alayrac, M; Marquis-Favre, C; Viollon, S; Morel, J; Le Nost, G

2010-09-01

In the study of noises generated by industrial sources, one issue is the variety of industrial noise sources and consequently the complexity of noises generated. Therefore, characterizing the environmental impact of an industrial plant requires better understanding of the noise annoyance caused by industrial noise sources. To deal with the variety of industrial sources, the proposed approach is set up by type of spectral features and based on a perceptive typology of steady and permanent industrial noises comprising six categories. For each perceptive category, listening tests based on acoustical factors are performed on noise annoyance. Various indicators are necessary to predict noise annoyance due to various industrial noise sources. Depending on the spectral features of the industrial noise sources, noise annoyance indicators are thus assessed. In case of industrial noise sources without main spectral features such as broadband noise, noise annoyance is predicted by the A-weighted sound pressure level L(Aeq) or the loudness level L(N). For industrial noises with spectral components such as low-frequency noises with a main component at 100 Hz or noises with spectral components in middle frequencies, indicators are proposed here that allow good prediction of noise annoyance by taking into account spectral features.

AN ELDERLY PATIENT WITH ACUTE TRANSIENT OUTER RETINAL DISRUPTION RESEMBLING BILATERAL MULTIPLE EVANESCENT WHITE DOT SYNDROME.

PubMed

Golshani, Cyrus; Gal-Or, Orly; Giovinazzo, Vincent; Freund, K Bailey

2017-11-07

To report an unusual case of an elderly patient with transient outer retinal disruption resembling bilateral multiple evanescent white dot syndrome. Observational case report. Fundus photographs, fluorescein angiography, standard and ultra-widefield fundus autofluorescence, and cross-sectional and en face optical coherence tomography were used to characterize and describe the clinical findings. A 67-year-old woman presented with decreased vision and floaters in her left eye. Best-corrected visual acuity was 20/20-3 in the right eye and 20/80-2 in the left eye. Funduscopic examination showed small deep white dots and foveal granularity of the left eye corresponding to hyperautofluorescent spots on fundus autofluorescence and ellipsoid zone disruption on spectral domain optical coherence tomography. The asymptomatic right eye had evidence of subretinal deposits on spectral domain optical coherence tomography but was otherwise unremarkable. At 4-week follow-up, the patient noted resolution of her symptoms in the left eye but had developed floaters and blurry vision in her right eye. The left eye showed resolving white spots and ellipsoid zone disruption. However, the right eye had new evidence of white spots corresponding to hyperautofluorescent spots on fundus autofluorescence. Spectral domain optical coherence tomography demonstrated subretinal deposits overlying areas of ellipsoid zone disruption. At 8-week follow-up, the patient was asymptomatic in both eyes with best-corrected visual acuity of 20/20 in both eyes. The hyperautofluorescent spots on ultra-widefield fundus autofluorescence had faded with restoration of ellipsoid zone disruption in both eyes and disappearance of subretinal deposits. Our case demonstrates multimodal retinal imaging findings resembling multiple evanescent white dot syndrome in an elderly patient. The bilateral presentation, presence of subretinal deposits before symptom onset, and older age of the patient were atypical features for this entity.

Evaluation of 1H NMR metabolic profiling using biofluid mixture design.

PubMed

Athersuch, Toby J; Malik, Shahid; Weljie, Aalim; Newton, Jack; Keun, Hector C

2013-07-16

A strategy for evaluating the performance of quantitative spectral analysis tools in conditions that better approximate background variation in a metabonomics experiment is presented. Three different urine samples were mixed in known proportions according to a {3, 3} simplex lattice experimental design and analyzed in triplicate by 1D (1)H NMR spectroscopy. Fifty-four urinary metabolites were subsequently quantified from the sample spectra using two methods common in metabolic profiling studies: (1) targeted spectral fitting and (2) targeted spectral integration. Multivariate analysis using partial least-squares (PLS) regression showed the latent structure of the spectral set recapitulated the experimental mixture design. The goodness-of-prediction statistic (Q(2)) of each metabolite variable in a PLS model was calculated as a metric for the reliability of measurement, across the sample compositional space. Several metabolites were observed to have low Q(2) values, largely as a consequence of their spectral resonances having low s/n or strong overlap with other sample components. This strategy has the potential to allow evaluation of spectral features obtained from metabolic profiling platforms in the context of the compositional background found in real biological sample sets, which may be subject to considerable variation. We suggest that it be incorporated into metabolic profiling studies to improve the estimation of matrix effects that confound accurate metabolite measurement. This novel method provides a rational basis for exploiting information from several samples in an efficient manner and avoids the use of multiple spike-in authentic standards, which may be difficult to obtain.

Investigation of the Spectroscopic Information on Functional Groups Related to Carbohydrates in Different Morphological Fractions of Corn Stover and Their Relationship to Nutrient Supply and Biodegradation Characteristics.

PubMed

Xin, Hangshu; Ding, Xue; Zhang, Liyang; Sun, Fang; Wang, Xiaofan; Zhang, Yonggen

2017-05-24

The objectives of this study were to investigate (1) nutritive values and biodegradation characteristics and (2) mid-IR spectroscopic features within the regions associated with carbohydrate functional groups (including cellulosic component (CELC), structural carbohydrate (STCHO), and total carbohydrate (CHO)) in different morphological fractions of corn stover. Furthermore, correlation and regression analyses were also applied to determine the relationship between nutritional values and spectroscopic parameters. The results showed that different morphological sections of corn stover had different nutrient supplies, in situ biodegradation characteristics, and spectral structural features within carbohydrate regions. The stem rind and ear husk were both high in fibrous content, which led to the lowest effective degradabilities (ED) among these stalk fractions. The ED values of NDF were ranked ear husk > stem pith > leaf blade > leaf sheath > whole plant > stem rind. Intensities of peak height and area within carbohydrate regions were relatively more stable compared with spectral ratio profiles. Significant difference was found only in peak area intensity of CELC, which was at the highest level for stem rind, followed by stem pith, leaf sheath, whole plant, leaf blade, and ear husk. Correlation results showed that changes in some carbohydrate spectral ratios were highly associated with carbohydrate chemical profiles and in situ rumen degradation kinetics. Among the various carbohydrate molecular spectral parameters that were tested in multiple regression analysis, CHO height ratios, and area ratios of CELC:CHO and CELC:STCHO as well as CELC area were mostly sensitive to nutrient supply and biodegradation characteristics in different morphological fractions of corn stover.

Spectral features of biogenic calcium carbonates and implications for astrobiology

NASA Astrophysics Data System (ADS)

Berg, B. L.; Ronholm, J.; Applin, D. M.; Mann, P.; Izawa, M.; Cloutis, E. A.; Whyte, L. G.

2014-09-01

The ability to discriminate biogenic from abiogenic calcium carbonate (CaCO3) would be useful in the search for extant or extinct life, since CaCO3 can be produced by both biotic and abiotic processes on Earth. Bioprecipitated CaCO3 material was produced during the growth of heterotrophic microbial isolates on medium enriched with calcium acetate or calcium citrate. These biologically produced CaCO3, along with natural and synthetic non-biologically produced CaCO3 samples, were analysed by reflectance spectroscopy (0.35-2.5 μm), Raman spectroscopy (532 and 785 nm), and laser-induced fluorescence spectroscopy (365 and 405 nm excitation). Optimal instruments for the discrimination of biogenic from abiogenic CaCO3 were determined to be reflectance spectroscopy, and laser-induced fluorescence spectroscopy. Multiple absorption features in the visible light region occurred in reflectance spectra for most biogenic CaCO3 samples, which are likely due to organic pigments. Multiple fluorescence peaks occurred in emission spectra (405 nm excitation) of biogenic CaCO3 samples, which also are best attributed to the presence of organic compounds; however, further analyses must be performed in order to better determine the cause of these features to establish criteria for confirming the origin of a given CaCO3 sample. Raman spectroscopy was not useful for discrimination since any potential Raman peaks in spectra of biogenic carbonates collected by both the 532 and 785 nm lasers were overwhelmed by fluorescence. However, this also suggests that biogenic carbonates may be identified by the presence of this organic-associated fluorescence. No reliable spectroscopic differences in terms of parameters such as positions or widths of carbonate-associated absorption bands were found between the biogenic and abiogenic carbonate samples. These results indicate that the presence or absence of organic matter intimately associated with carbonate minerals is the only potentially useful spectral discriminator for the techniques that were examined, and that multiple spectroscopic techniques are capable of detecting the presence of associated organic materials. However, the presence or absence of intimately associated organic matter is not, in itself, an indicator of biogenicity.

Use of feature extraction techniques for the texture and context information in ERTS imagery: Spectral and textural processing of ERTS imagery. [classification of Kansas land use

NASA Technical Reports Server (NTRS)

Haralick, R. H. (Principal Investigator); Bosley, R. J.

1974-01-01

The author has identified the following significant results. A procedure was developed to extract cross-band textural features from ERTS MSS imagery. Evolving from a single image texture extraction procedure which uses spatial dependence matrices to measure relative co-occurrence of nearest neighbor grey tones, the cross-band texture procedure uses the distribution of neighboring grey tone N-tuple differences to measure the spatial interrelationships, or co-occurrences, of the grey tone N-tuples present in a texture pattern. In both procedures, texture is characterized in such a way as to be invariant under linear grey tone transformations. However, the cross-band procedure complements the single image procedure by extracting texture information and spectral information contained in ERTS multi-images. Classification experiments show that when used alone, without spectral processing, the cross-band texture procedure extracts more information than the single image texture analysis. Results show an improvement in average correct classification from 86.2% to 88.8% for ERTS image no. 1021-16333 with the cross-band texture procedure. However, when used together with spectral features, the single image texture plus spectral features perform better than the cross-band texture plus spectral features, with an average correct classification of 93.8% and 91.6%, respectively.

Low complexity feature extraction for classification of harmonic signals

NASA Astrophysics Data System (ADS)

William, Peter E.

In this dissertation, feature extraction algorithms have been developed for extraction of characteristic features from harmonic signals. The common theme for all developed algorithms is the simplicity in generating a significant set of features directly from the time domain harmonic signal. The features are a time domain representation of the composite, yet sparse, harmonic signature in the spectral domain. The algorithms are adequate for low-power unattended sensors which perform sensing, feature extraction, and classification in a standalone scenario. The first algorithm generates the characteristic features using only the duration between successive zero-crossing intervals. The second algorithm estimates the harmonics' amplitudes of the harmonic structure employing a simplified least squares method without the need to estimate the true harmonic parameters of the source signal. The third algorithm, resulting from a collaborative effort with Daniel White at the DSP Lab, University of Nebraska-Lincoln, presents an analog front end approach that utilizes a multichannel analog projection and integration to extract the sparse spectral features from the analog time domain signal. Classification is performed using a multilayer feedforward neural network. Evaluation of the proposed feature extraction algorithms for classification through the processing of several acoustic and vibration data sets (including military vehicles and rotating electric machines) with comparison to spectral features shows that, for harmonic signals, time domain features are simpler to extract and provide equivalent or improved reliability over the spectral features in both the detection probabilities and false alarm rate.

Structural biomechanics determine spectral purity of bush-cricket calls.

PubMed

Chivers, Benedict D; Jonsson, Thorin; Soulsbury, Carl D; Montealegre-Z, Fernando

2017-11-01

Bush-crickets (Orthoptera: Tettigoniidae) generate sound using tegminal stridulation. Signalling effectiveness is affected by the widely varying acoustic parameters of temporal pattern, frequency and spectral purity (tonality). During stridulation, frequency multiplication occurs as a scraper on one wing scrapes across a file of sclerotized teeth on the other. The frequency with which these tooth-scraper interactions occur, along with radiating wing cell resonant properties, dictates both frequency and tonality in the call. Bush-cricket species produce calls ranging from resonant, tonal calls through to non-resonant, broadband signals. The differences are believed to result from differences in file tooth arrangement and wing radiators, but a systematic test of the structural causes of broadband or tonal calls is lacking. Using phylogenetically controlled structural equation models, we show that parameters of file tooth density and file length are the best-fitting predictors of tonality across 40 bush-cricket species. Features of file morphology constrain the production of spectrally pure signals, but systematic distribution of teeth alone does not explain pure-tone sound production in this family. © 2017 The Authors.

Structural biomechanics determine spectral purity of bush-cricket calls

PubMed Central

2017-01-01

Bush-crickets (Orthoptera: Tettigoniidae) generate sound using tegminal stridulation. Signalling effectiveness is affected by the widely varying acoustic parameters of temporal pattern, frequency and spectral purity (tonality). During stridulation, frequency multiplication occurs as a scraper on one wing scrapes across a file of sclerotized teeth on the other. The frequency with which these tooth–scraper interactions occur, along with radiating wing cell resonant properties, dictates both frequency and tonality in the call. Bush-cricket species produce calls ranging from resonant, tonal calls through to non-resonant, broadband signals. The differences are believed to result from differences in file tooth arrangement and wing radiators, but a systematic test of the structural causes of broadband or tonal calls is lacking. Using phylogenetically controlled structural equation models, we show that parameters of file tooth density and file length are the best-fitting predictors of tonality across 40 bush-cricket species. Features of file morphology constrain the production of spectrally pure signals, but systematic distribution of teeth alone does not explain pure-tone sound production in this family. PMID:29187608

Bloodstain detection and discrimination impacted by spectral shift when using an interference filter-based visible and near-infrared multispectral crime scene imaging system

NASA Astrophysics Data System (ADS)

Yang, Jie; Messinger, David W.; Dube, Roger R.

2018-03-01

Bloodstain detection and discrimination from nonblood substances on various substrates are critical in forensic science as bloodstains are a critical source for confirmatory DNA tests. Conventional bloodstain detection methods often involve time-consuming sample preparation, a chance of harm to investigators, the possibility of destruction of blood samples, and acquisition of too little data at crime scenes either in the field or in the laboratory. An imaging method has the advantages of being nondestructive, noncontact, real-time, and covering a large field-of-view. The abundant spectral information provided by multispectral imaging makes it a potential presumptive bloodstain detection and discrimination method. This article proposes an interference filter (IF) based area scanning three-spectral-band crime scene imaging system used for forensic bloodstain detection and discrimination. The impact of large angle of views on the spectral shift of calibrated IFs is determined, for both detecting and discriminating bloodstains from visually similar substances on multiple substrates. Spectral features in the visible and near-infrared portion employed by the relative band depth method are used. This study shows that 1 ml bloodstain on black felt, gray felt, red felt, white cotton, white polyester, and raw wood can be detected. Bloodstains on the above substrates can be discriminated from cola, coffee, ketchup, orange juice, red wine, and green tea.

Spectral-spatial classification of hyperspectral data with mutual information based segmented stacked autoencoder approach

NASA Astrophysics Data System (ADS)

Paul, Subir; Nagesh Kumar, D.

2018-04-01

Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow spectral bands with very fine spectral resolution or bandwidth, which offer feature identification and classification with high accuracy. In the present study, Mutual Information (MI) based Segmented Stacked Autoencoder (S-SAE) approach for spectral-spatial classification of the HS data is proposed to reduce the complexity and computational time compared to Stacked Autoencoder (SAE) based feature extraction. A non-parametric dependency measure (MI) based spectral segmentation is proposed instead of linear and parametric dependency measure to take care of both linear and nonlinear inter-band dependency for spectral segmentation of the HS bands. Then morphological profiles are created corresponding to segmented spectral features to assimilate the spatial information in the spectral-spatial classification approach. Two non-parametric classifiers, Support Vector Machine (SVM) with Gaussian kernel and Random Forest (RF) are used for classification of the three most popularly used HS datasets. Results of the numerical experiments carried out in this study have shown that SVM with a Gaussian kernel is providing better results for the Pavia University and Botswana datasets whereas RF is performing better for Indian Pines dataset. The experiments performed with the proposed methodology provide encouraging results compared to numerous existing approaches.

Radio-nuclide mixture identification using medium energy resolution detectors

DOEpatents

Nelson, Karl Einar

2013-09-17

According to one embodiment, a method for identifying radio-nuclides includes receiving spectral data, extracting a feature set from the spectral data comparable to a plurality of templates in a template library, and using a branch and bound method to determine a probable template match based on the feature set and templates in the template library. In another embodiment, a device for identifying unknown radio-nuclides includes a processor, a multi-channel analyzer, and a memory operatively coupled to the processor, the memory having computer readable code stored thereon. The computer readable code is configured, when executed by the processor, to receive spectral data, to extract a feature set from the spectral data comparable to a plurality of templates in a template library, and to use a branch and bound method to determine a probable template match based on the feature set and templates in the template library.

Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

PubMed

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-10-23

A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

Plant Leaf Chlorophyll Content Retrieval Based on a Field Imaging Spectroscopy System

PubMed Central

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-01-01

A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector. PMID:25341439

Assessment of seasonal features based on Landsat time series for tree crown cover mapping in Burkina Faso

NASA Astrophysics Data System (ADS)

Liu, Jinxiu; Heiskanen, Janne; Aynekuly, Ermias; Pellikka, Petri

2016-04-01

Tree crown cover (CC) is an important vegetation attribute for land cover characterization, and for mapping and monitoring forest cover. Free data from Landsat and Sentinel-2 allow construction of fine resolution satellite image time series and extraction of seasonal features for predicting vegetation attributes. In the savannas, surface reflectance vary distinctively according to the rainy and dry seasons, and seasonal features are useful information for CC mapping. However, it is unclear if it is better to use spectral bands or vegetation indices (VI) for computation of seasonal features, and how feasible different VI are for CC prediction in the savanna woodlands and agroforestry parklands of West Africa. In this study, the objective was to compare seasonal features based on spectral bands and VI for CC mapping in southern Burkina Faso. A total of 35 Landsat images from November 2013 to October 2014 were processed. Seasonal features were computed using a harmonic model with three parameters (mean, amplitude and phase), and spectral bands, normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), normalized difference water index (NDWI), tasseled cap (TC) indices (brightness, greenness, wetness) as input data. The seasonal features were employed to predict field estimated CC (n = 160) using Random Forest algorithm. The most accurate results were achieved when using seasonal features based on TC indices (R2: 0.65; RMSE: 10.7%) and spectral bands (R2: 0.64; RMSE: 10.8%). GNDVI performed better than NDVI or NDWI, and NDWI resulted in the poorest results (R2: 0.56; RMSE: 11.9%). The results indicate that spectral features should be carefully selected for CC prediction as shown by relatively poor performance of commonly used NDVI. The seasonal features based on three TC indices and all the spectral bands provided superior accuracy in comparison to single VI. The method presented in this study provides a feasible method to map CC based on seasonal features with possibility to integrate medium resolution satellite observation from several sensors (e.g. Landsat and Sentinel-2) in the future.

Application of Multi-task Lasso Regression in the Parametrization of Stellar Spectra

NASA Astrophysics Data System (ADS)

Chang, Li-Na; Zhang, Pei-Ai

2015-07-01

The multi-task learning approaches have attracted the increasing attention in the fields of machine learning, computer vision, and artificial intelligence. By utilizing the correlations in tasks, learning multiple related tasks simultaneously is better than learning each task independently. An efficient multi-task Lasso (Least Absolute Shrinkage Selection and Operator) regression algorithm is proposed in this paper to estimate the physical parameters of stellar spectra. It not only can obtain the information about the common features of the different physical parameters, but also can preserve effectively their own peculiar features. Experiments were done based on the ELODIE synthetic spectral data simulated with the stellar atmospheric model, and on the SDSS data released by the American large-scale survey Sloan. The estimation precision of our model is better than those of the methods in the related literature, especially for the estimates of the gravitational acceleration (lg g) and the chemical abundance ([Fe/H]). In the experiments we changed the spectral resolution, and applied the noises with different signal-to-noise ratios (SNRs) to the spectral data, so as to illustrate the stability of the model. The results show that the model is influenced by both the resolution and the noise. But the influence of the noise is larger than that of the resolution. In general, the multi-task Lasso regression algorithm is easy to operate, it has a strong stability, and can also improve the overall prediction accuracy of the model.

Silica-rich deposits and hydrated minerals at Gusev Crater, Mars: Vis-NIR spectral characterization and regional mapping

USGS Publications Warehouse

Rice, M.S.; Bell, J.F.; Cloutis, E.A.; Wang, A.; Ruff, S.W.; Craig, M.A.; Bailey, D.T.; Johnson, J. R.; De Souza, P.A.; Farrand, W. H.

2010-01-01

The Mars Exploration Rover (MER) Spirit has discovered surprisingly high concentrations of amorphous silica in soil and nodular outcrops in the Inner Basin of the Columbia Hills. In Pancam multispectral observations, we find that an absorption feature at the longest Pancam wavelength (1009 nm) appears to be characteristic of these silica-rich materials; however, spectral analyses of amorphous silica suggest that the ???1009 nm spectral feature is not a direct reflection of their silica-rich nature. Based on comparisons with spectral databases, we hypothesize that the presence of H2O or OH, either free (as water ice), adsorbed or bound in a mineral structure, is responsible for the spectral feature observed by Pancam. The Gertrude Weise soil, which is nearly pure opaline silica, may have adsorbed water cold-trapped on mineral grains. The origin of the ???1009 nm Pancam feature observed in the silica-rich nodular outcrops may result from the presence of additional hydrated minerals (specific sulfates, halides, chlorides, sodium silicates, carbonates or borates). Using the ???1009 nm feature with other spectral parameters as a "hydration signature" we have mapped the occurrence of hydrated materials along the extent of Spirit's traverse across the Columbia Hills from West Spur to Home Plate (sols 155-1696). We have also mapped this hydration signature across large panoramic images to understand the regional distribution of materials that are spectrally similar to the silica-rich soil and nodular outcrops. Our results suggest that hydrated materials are common in the Columbia Hills. ?? 2009 Elsevier Inc.

Mapping accuracy via spectrally and structurally based filtering techniques: comparisons through visual observations

NASA Astrophysics Data System (ADS)

Chockalingam, Letchumanan

2005-01-01

The data of Gunung Ledang region of Malaysia acquired through LANDSAT are considered to map certain hydrogeolocial features. To map these significant features, image-processing tools such as contrast enhancement, edge detection techniques are employed. The advantages of these techniques over the other methods are evaluated from the point of their validity in properly isolating features of hydrogeolocial interest are discussed. As these techniques take the advantage of spectral aspects of the images, these techniques have several limitations to meet the objectives. To discuss these limitations, a morphological transformation, which generally considers the structural aspects rather than spectral aspects from the image, are applied to provide comparisons between the results derived from spectral based and the structural based filtering techniques.

An Exercise on Calibration: DRIFTS Study of Binary Mixtures of Calcite and Dolomite with Partially Overlapping Spectral Features

ERIC Educational Resources Information Center

De Lorenzi Pezzolo, Alessandra

2013-01-01

Unlike most spectroscopic calibrations that are based on the study of well-separated features ascribable to the different components, this laboratory experience is especially designed to exploit spectral features that are nearly overlapping. The investigated system consists of a binary mixture of two commonly occurring minerals, calcite and…

Deep Learning Based Binaural Speech Separation in Reverberant Environments.

PubMed

Zhang, Xueliang; Wang, DeLiang

2017-05-01

Speech signal is usually degraded by room reverberation and additive noises in real environments. This paper focuses on separating target speech signal in reverberant conditions from binaural inputs. Binaural separation is formulated as a supervised learning problem, and we employ deep learning to map from both spatial and spectral features to a training target. With binaural inputs, we first apply a fixed beamformer and then extract several spectral features. A new spatial feature is proposed and extracted to complement the spectral features. The training target is the recently suggested ideal ratio mask. Systematic evaluations and comparisons show that the proposed system achieves very good separation performance and substantially outperforms related algorithms under challenging multi-source and reverberant environments.

Status of the NPP and J1 NOAA Unique Combined Atmospheric Processing System (NUCAPS): recent algorithm enhancements geared toward validation and near real time users applications.

NASA Astrophysics Data System (ADS)

Gambacorta, A.; Nalli, N. R.; Tan, C.; Iturbide-Sanchez, F.; Wilson, M.; Zhang, K.; Xiong, X.; Barnet, C. D.; Sun, B.; Zhou, L.; Wheeler, A.; Reale, A.; Goldberg, M.

2017-12-01

The NOAA Unique Combined Atmospheric Processing System (NUCAPS) is the NOAA operational algorithm to retrieve thermodynamic and composition variables from hyper spectral thermal sounders such as CrIS, IASI and AIRS. The combined use of microwave sounders, such as ATMS, AMSU and MHS, enables full atmospheric sounding of the atmospheric column under all-sky conditions. NUCAPS retrieval products are accessible in near real time (about 1.5 hour delay) through the NOAA Comprehensive Large Array-data Stewardship System (CLASS). Since February 2015, NUCAPS retrievals have been also accessible via Direct Broadcast, with unprecedented low latency of less than 0.5 hours. NUCAPS builds on a long-term, multi-agency investment on algorithm research and development. The uniqueness of this algorithm consists in a number of features that are key in providing highly accurate and stable atmospheric retrievals, suitable for real time weather and air quality applications. Firstly, maximizing the use of the information content present in hyper spectral thermal measurements forms the foundation of the NUCAPS retrieval algorithm. Secondly, NUCAPS is a modular, name-list driven design. It can process multiple hyper spectral infrared sounders (on Aqua, NPP, MetOp and JPSS series) by mean of the same exact retrieval software executable and underlying spectroscopy. Finally, a cloud-clearing algorithm and a synergetic use of microwave radiance measurements enable full vertical sounding of the atmosphere, under all-sky regimes. As we transition toward improved hyper spectral missions, assessing retrieval skill and consistency across multiple platforms becomes a priority for real time users applications. Focus of this presentation is a general introduction on the recent improvements in the delivery of the NUCAPS full spectral resolution upgrade and an overview of the lessons learned from the 2017 Hazardous Weather Test bed Spring Experiment. Test cases will be shown on the use of NPP and MetOp NUCAPS under pre-convective, capping inversion and dry layer intrusion events.

The Colorado Ultraviolet Transit Experiment (CUTE): Observing Mass Loss on Short-Period Exoplanets

NASA Astrophysics Data System (ADS)

Egan, Arika; Fleming, Brian; France, Kevin

2018-06-01

The Colorado Ultraviolet Transit Experiment (CUTE) is an NUV spectrograph packaged into a 6U CubeSat, designed to characterize the interaction between exoplanetary atmospheres and their host stars. CUTE will conduct a transit spectroscopy survey, gathering data over multiple transits on more than 12 short-period exoplanets with a range of masses and radii. The instrument will characterize the spectral properties of the transit light curves to < 1% depth sensitivity. The NUV is host to several high oscillator strength atomic and molecular absorption features predicted to exist in the upper atmospheres of these planets, including Mg I, Mg II, Fe II, and OH. The shape and evolution of these spectral light curves will be used to quantify mass loss rates, the stellar drives of that mass loss, and the possible existence of exoplanetary magnetic fiends. This poster presents the science motivation for CUTE, planned observation and data analysis methods, and expected results.

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

A LANDSAT study of ephemeral and perennial rangeland vegetation and soils

NASA Technical Reports Server (NTRS)

Bentley, R. G., Jr. (Principal Investigator); Salmon-Drexler, B. C.; Bonner, W. J.; Vincent, R. K.

1976-01-01

The author has identified the following significant results. Several methods of computer processing were applied to LANDSAT data for mapping vegetation characteristics of perennial rangeland in Montana and ephemeral rangeland in Arizona. The choice of optimal processing technique was dependent on prescribed mapping and site condition. Single channel level slicing and ratioing of channels were used for simple enhancement. Predictive models for mapping percent vegetation cover based on data from field spectra and LANDSAT data were generated by multiple linear regression of six unique LANDSAT spectral ratios. Ratio gating logic and maximum likelihood classification were applied successfully to recognize plant communities in Montana. Maximum likelihood classification did little to improve recognition of terrain features when compared to a single channel density slice in sparsely vegetated Arizona. LANDSAT was found to be more sensitive to differences between plant communities based on percentages of vigorous vegetation than to actual physical or spectral differences among plant species.

Inspection of baked carbon anodes using a combination of multi-spectral acousto-ultrasonic techniques and principal component analysis.

PubMed

Boubaker, Moez Ben; Picard, Donald; Duchesne, Carl; Tessier, Jayson; Alamdari, Houshang; Fafard, Mario

2018-05-17

This paper reports on the application of an acousto-ultrasonic (AU) scheme for the inspection of industrial-size carbon anode blocks used in the production of primary aluminium by the Hall-Héroult process. A frequency-modulated wave is used to excite the anode blocks at multiple points. The collected attenuated AU signals are decomposed using the Discrete Wavelet Transform (DTW) after which vectors of features are calculated. Principal Component Analysis (PCA) is utilized to cluster the AU responses of the anodes. The approach allows locating cracks in the blocks and the AU features were found sensitive to crack severity. The results are validated using images collected after cutting some anodes. Copyright © 2018 Elsevier B.V. All rights reserved.

Hyper sausage neuron: Recognition of transgenic sugar-beet based on terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Li, Zhi; Hu, Fangrong; Chen, Tao; Du, Yong; Xin, Haitao

2015-01-01

This paper presents a novel approach for identification of terahertz (THz) spectral of genetically modified organisms (GMOs) based on Hyper Sausage Neuron (HSN), and THz transmittance spectra of some typical transgenic sugar-beet samples are investigated to demonstrate its feasibility. Principal component analysis (PCA) is applied to extract features of the spectrum data, and instead of the original spectrum data, the feature signals are fed into the HSN pattern recognition, a new multiple weights neural network (MWNN). The experimental result shows that the HSN model not only can correctly classify different types of transgenic sugar-beets, but also can reject identity non similar samples in the same type. The proposed approach provides a new effective method for detection and identification of GMOs by using THz spectroscopy.

Sheath field dynamics from time-dependent acceleration of laser-generated positrons

NASA Astrophysics Data System (ADS)

Kerr, Shaun; Fedosejevs, Robert; Link, Anthony; Williams, Jackson; Park, Jaebum; Chen, Hui

2017-10-01

Positrons produced in ultraintense laser-matter interactions are accelerated by the sheath fields established by fast electrons, typically resulting in quasi-monoenergetic beams. Experimental results from OMEGA EP show higher order features developing in the positron spectra when the laser energy exceeds one kilojoule. 2D PIC simulations using the LSP code were performed to give insight into these spectral features. They suggest that for high laser energies multiple, distinct phases of acceleration can occur due to time-dependent sheath field acceleration. The detailed dynamics of positron acceleration will be discussed. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344, and funded by LDRD 17-ERD-010.

Decoding visual object categories from temporal correlations of ECoG signals.

PubMed

Majima, Kei; Matsuo, Takeshi; Kawasaki, Keisuke; Kawai, Kensuke; Saito, Nobuhito; Hasegawa, Isao; Kamitani, Yukiyasu

2014-04-15

How visual object categories are represented in the brain is one of the key questions in neuroscience. Studies on low-level visual features have shown that relative timings or phases of neural activity between multiple brain locations encode information. However, whether such temporal patterns of neural activity are used in the representation of visual objects is unknown. Here, we examined whether and how visual object categories could be predicted (or decoded) from temporal patterns of electrocorticographic (ECoG) signals from the temporal cortex in five patients with epilepsy. We used temporal correlations between electrodes as input features, and compared the decoding performance with features defined by spectral power and phase from individual electrodes. While using power or phase alone, the decoding accuracy was significantly better than chance, correlations alone or those combined with power outperformed other features. Decoding performance with correlations was degraded by shuffling the order of trials of the same category in each electrode, indicating that the relative time series between electrodes in each trial is critical. Analysis using a sliding time window revealed that decoding performance with correlations began to rise earlier than that with power. This earlier increase in performance was replicated by a model using phase differences to encode categories. These results suggest that activity patterns arising from interactions between multiple neuronal units carry additional information on visual object categories. Copyright © 2013 Elsevier Inc. All rights reserved.

A spectral-structural bag-of-features scene classifier for very high spatial resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei

2016-06-01

Land-use classification of very high spatial resolution remote sensing (VHSR) imagery is one of the most challenging tasks in the field of remote sensing image processing. However, the land-use classification is hard to be addressed by the land-cover classification techniques, due to the complexity of the land-use scenes. Scene classification is considered to be one of the expected ways to address the land-use classification issue. The commonly used scene classification methods of VHSR imagery are all derived from the computer vision community that mainly deal with terrestrial image recognition. Differing from terrestrial images, VHSR images are taken by looking down with airborne and spaceborne sensors, which leads to the distinct light conditions and spatial configuration of land cover in VHSR imagery. Considering the distinct characteristics, two questions should be answered: (1) Which type or combination of information is suitable for the VHSR imagery scene classification? (2) Which scene classification algorithm is best for VHSR imagery? In this paper, an efficient spectral-structural bag-of-features scene classifier (SSBFC) is proposed to combine the spectral and structural information of VHSR imagery. SSBFC utilizes the first- and second-order statistics (the mean and standard deviation values, MeanStd) as the statistical spectral descriptor for the spectral information of the VHSR imagery, and uses dense scale-invariant feature transform (SIFT) as the structural feature descriptor. From the experimental results, the spectral information works better than the structural information, while the combination of the spectral and structural information is better than any single type of information. Taking the characteristic of the spatial configuration into consideration, SSBFC uses the whole image scene as the scope of the pooling operator, instead of the scope generated by a spatial pyramid (SP) commonly used in terrestrial image classification. The experimental results show that the whole image as the scope of the pooling operator performs better than the scope generated by SP. In addition, SSBFC codes and pools the spectral and structural features separately to avoid mutual interruption between the spectral and structural features. The coding vectors of spectral and structural features are then concatenated into a final coding vector. Finally, SSBFC classifies the final coding vector by support vector machine (SVM) with a histogram intersection kernel (HIK). Compared with the latest scene classification methods, the experimental results with three VHSR datasets demonstrate that the proposed SSBFC performs better than the other classification methods for VHSR image scenes.

Nonlinear photothermal mid-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Totachawattana, Atcha; Erramilli, Shyamsunder; Sander, Michelle Y.

2016-10-01

Mid-infrared photothermal spectroscopy is a pump-probe technique for label-free and non-destructive sample characterization by targeting intrinsic vibrational modes. In this method, the mid-infrared pump beam excites a temperature-induced change in the refractive index of the sample. This laser-induced change in the refractive index is measured by a near-infrared probe laser using lock-in detection. At increased pump powers, emerging nonlinear phenomena not previously demonstrated in other mid-infrared techniques are observed. Nonlinear study of a 6 μm-thick 4-Octyl-4'-Cyanobiphenyl (8CB) liquid crystal sample is conducted by targeting the C=C stretching band at 1606 cm-1. At high pump powers, nonlinear signal enhancement and multiple pitchfork bifurcations of the spectral features are observed. An explanation of the nonlinear peak splitting is provided by the formation of bubbles in the sample at high pump powers. The discontinuous refractive index across the bubble interface results in a decrease in the forward scatter of the probe beam. This effect can be recorded as a bifurcation of the absorption peak in the photothermal spectrum. These nonlinear effects are not present in direct measurements of the mid-infrared beam. Evolution of the nonlinear photothermal spectrum of 8CB liquid crystal with increasing pump power shows enhancement of the absorption peak at 1606 cm-1. Multiple pitchfork bifurcations and spectral narrowing of the photothermal spectrum are demonstrated. This novel nonlinear regime presents potential for improved spectral resolution as well as a new regime for sample characterization in mid-infrared photothermal spectroscopy.

Astrophysical data on 5 eV to 1 keV radiation from the radiative decay of fundamental particles - Current limits and prospects for improvement

NASA Technical Reports Server (NTRS)

Bowyer, Stuart; Malina, Roger F.

1986-01-01

Line emission from the decay of fundamental particles, integrated over cosmological distances, can give rise to detectable spectral features in the diffuse astronomical background between 5 eV and 1 keV. Spectroscopic observations may allow these features to be separated from line emission from the numerous local sources of radiation. The current observational status and existing evidence for such features are reviewed. No definitive detections of nongalactic line features have been made. Several local sources of background mask the features at many wavelengths and confuse the interpretation of the data. No systematic spectral observations have been carried out to date. Upcoming experiments which can be expected to provide significantly better constraints on the presence of spectral features in the diffuse background from 5 eV to 1 keV are reviewed.

Spectral feature variations in x-ray diffraction imaging systems

NASA Astrophysics Data System (ADS)

Wolter, Scott D.; Greenberg, Joel A.

2016-05-01

Materials with different atomic or molecular structures give rise to unique scatter spectra when measured by X-ray diffraction. The details of these spectra, though, can vary based on both intrinsic (e.g., degree of crystallinity or doping) and extrinsic (e.g., pressure or temperature) conditions. While this sensitivity is useful for detailed characterizations of the material properties, these dependences make it difficult to perform more general classification tasks, such as explosives threat detection in aviation security. A number of challenges, therefore, currently exist for reliable substance detection including the similarity in spectral features among some categories of materials combined with spectral feature variations from materials processing and environmental factors. These factors complicate the creation of a material dictionary and the implementation of conventional classification and detection algorithms. Herein, we report on two prominent factors that lead to variations in spectral features: crystalline texture and temperature variations. Spectral feature comparisons between materials categories will be described for solid metallic sheet, aqueous liquids, polymer sheet, and metallic, organic, and inorganic powder specimens. While liquids are largely immune to texture effects, they are susceptible to temperature changes that can modify their density or produce phase changes. We will describe in situ temperature-dependent measurement of aqueous-based commercial goods in the temperature range of -20°C to 35°C.

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

PubMed

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

Luciferase-Specific Coelenterazine Analogues for Optical Contamination-Free Bioassays.

PubMed

Nishihara, Ryo; Abe, Masahiro; Nishiyama, Shigeru; Citterio, Daniel; Suzuki, Koji; Kim, Sung Bae

2017-04-19

Spectral overlaps among the multiple optical readouts commonly cause optical contamination in fluorescence and bioluminescence. To tackle this issue, we created five-different lineages of coelenterazine (CTZ) analogues designed to selectively illuminate a specific luciferase with unique luciferase selectivity. In the attempt, we found that CTZ analogues with ethynyl or styryl groups display dramatically biased bioluminescence to specific luciferases and pHs by modifying the functional groups at the C-2 and C-6 positions of the imidazopyradinone backbone of CTZ. The optical contamination-free feature was exemplified with the luciferase-specific CTZ analogues, which illuminated anti-estrogenic and rapamycin activities in a mixture of optical probes. This unique bioluminescence platform has great potential for specific and high throughput imaging of multiple optical readouts in bioassays without optical contamination.

Use of feature extraction techniques for the texture and context information in ERTS imagery. [discrimination of land use categories in Kansas from MSS textural-spectral features

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Kelly, G. L. (Principal Investigator); Bosley, R. J.

1973-01-01

The author has identified the following significant results. The land use category of subimage regions over Kansas within an MSS image can be identified with an accuracy of about 70% using the textural-spectral features of the multi-images from the four MSS bands.

GENIE: a hybrid genetic algorithm for feature classification in multispectral images

NASA Astrophysics Data System (ADS)

Perkins, Simon J.; Theiler, James P.; Brumby, Steven P.; Harvey, Neal R.; Porter, Reid B.; Szymanski, John J.; Bloch, Jeffrey J.

2000-10-01

We consider the problem of pixel-by-pixel classification of a multi- spectral image using supervised learning. Conventional spuervised classification techniques such as maximum likelihood classification and less conventional ones s uch as neural networks, typically base such classifications solely on the spectral components of each pixel. It is easy to see why: the color of a pixel provides a nice, bounded, fixed dimensional space in which these classifiers work well. It is often the case however, that spectral information alone is not sufficient to correctly classify a pixel. Maybe spatial neighborhood information is required as well. Or maybe the raw spectral components do not themselves make for easy classification, but some arithmetic combination of them would. In either of these cases we have the problem of selecting suitable spatial, spectral or spatio-spectral features that allow the classifier to do its job well. The number of all possible such features is extremely large. How can we select a suitable subset? We have developed GENIE, a hybrid learning system that combines a genetic algorithm that searches a space of image processing operations for a set that can produce suitable feature planes, and a more conventional classifier which uses those feature planes to output a final classification. In this paper we show that the use of a hybrid GA provides significant advantages over using either a GA alone or more conventional classification methods alone. We present results using high-resolution IKONOS data, looking for regions of burned forest and for roads.

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

PubMed Central

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-01-01

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification. PMID:28025525

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

PubMed

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.

Preliminary results from an investigation of AIS-1 data over an area of epithermal alteration: Plateau, Northern Queensland, Australia

NASA Technical Reports Server (NTRS)

Mackin, Steve; Munday, Tim; Hook, Simon

1987-01-01

Airborne Imaging Spectrometer-1 (AIS-1) data were flown over undifferentiated sequences of acid to intermediate volcanics and intrusives; meta-sediments; and a series of partially lateritized sedimentary rocks. The area exhibits a considerable spectral variability, after the suppression of striping effects. Log residual, and Internal Average Relative Reflectance (IARR) analytical techniques were used to enhance mineralogically related spectral features. Both methods produce similar results, but did not visually highlight mineral absorption features due to processing artifacts in areas of significant vegetation cover. The enhancement of mineral related absorption features was achieved using a hybrid processing approach based on the relative reflectance differences between vegetated and non-vegetated surfaces at 1.2 and 2.1 micron. The result is an image with little overall contrast, but which enhances the more subtle spectral features believed to be associated with clays and epidote. The AIS data was subject to interactive analysis using SPAM. Clear separation of clay and epidote related absorption features was apparent, and the identification of kaolinite was possible despite detrimental spectral effects.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Spectral reflectance and emissivity features of broad leaf plants: Prospects for remote sensing in the thermal infrared (8.0-14.0 μm)

USGS Publications Warehouse

Ribeiro da Luz, Beatriz; Crowley, James K.

2007-01-01

In contrast to visible and short-wave infrared data, thermal infrared spectra of broad leaf plants show considerable spectral diversity, suggesting that such data eventually could be utilized to map vegetation composition. However, remotely measuring the subtle emissivity features of leaves still presents major challenges. To be successful, sensors operating in the 8–14 μm atmospheric window must have high signal-to-noise and a small enough instantaneous field of view to allow measurements of only a few leaf surfaces. Methods for atmospheric compensation, temperature–emissivity separation, and spectral feature analysis also will need to be refined to allow the recognition, and perhaps, exploitation of leaf thermal infrared spectral properties.

Reflectance spectroscopy (0.35-8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids

NASA Astrophysics Data System (ADS)

Berg, Breanne L.; Cloutis, Edward A.; Beck, Pierre; Vernazza, Pierre; Bishop, Janice L.; Takir, Driss; Reddy, Vishnu; Applin, Daniel; Mann, Paul

2016-02-01

Ammonium-bearing minerals have been suggested to be present on Mars, Ceres, and various asteroids and comets. We undertook a systematic study of the spectral reflectance properties of ammonium-bearing minerals and compounds that have possible planetary relevance (i.e., ammonium carbonates, chlorides, nitrates, oxalates, phosphates, silicates, and sulfates). Various synthetic and natural NH4+-bearing minerals were analyzed using reflectance spectroscopy in the long-wave ultraviolet, visible, near-infrared, and mid-infrared regions (0.35-8 μm) in order to identify spectral features characteristic of the NH4+ molecule, and to evaluate if and how these features vary among different species. Mineral phases were confirmed through structural and compositional analyses using X-ray diffraction, X-ray fluorescence, and elemental combustion analysis. Characteristic absorption features associated with NH4 can be seen in the reflectance spectra at wavelengths as short as ∼1 μm. In the near-infrared region, the most prominent absorption bands are located near 1.6, 2.0, and 2.2 μm. Absorption features characteristic of NH4+ occurred at slightly longer wavelengths in the mineral-bound NH4+ spectra than for free NH4+ for most of the samples. Differences in wavelength position are attributable to various factors, including differences in the type and polarizability of the anion(s) attached to the NH4+, degree and type of hydrogen bonding, molecule symmetry, and cation substitutions. Multiple absorption features, usually three absorption bands, in the mid-infrared region between ∼2.8 and 3.8 μm were seen in all but the most NH4-poor sample spectra, and are attributed to fundamentals, combinations, and overtones of stretching and bending vibrations of the NH4+ molecule. These features appear even in reflectance spectra of water-rich samples which exhibit a strong 3 μm region water absorption feature. While many of the samples examined in this study have NH4 absorption bands at unique wavelength positions, in order to discriminate between different NH4+-bearing phases, absorption features corresponding to molecules other than NH4+ should be included in spectral analysis. A qualitative comparison of the laboratory results to telescopic spectra of Asteroids 1 Ceres, 10 Hygiea, and 324 Bamberga for the 3 μm region demonstrates that a number of NH4-bearing phases are consistent with the observational data in terms of exhibiting an absorption band in the 3.07 μm region.

Reflectance spectroscopy (0.35–8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids

USGS Publications Warehouse

Berg, Breanne L.; Cloutis, Edward A.; Beck, P.; Vernazza, P.; Bishop, Janice L; Takir, Driss; Reddy, V.; Applin, D.; Mann, Paul

2016-01-01

Ammonium-bearing minerals have been suggested to be present on Mars, Ceres, and various asteroids and comets. We undertook a systematic study of the spectral reflectance properties of ammonium-bearing minerals and compounds that have possible planetary relevance (i.e., ammonium carbonates, chlorides, nitrates, oxalates, phosphates, silicates, and sulfates). Various synthetic and natural NH4+-bearing minerals were analyzed using reflectance spectroscopy in the long-wave ultraviolet, visible, near-infrared, and mid-infrared regions (0.35–8 μm) in order to identify spectral features characteristic of the NH4+ molecule, and to evaluate if and how these features vary among different species. Mineral phases were confirmed through structural and compositional analyses using X-ray diffraction, X-ray fluorescence, and elemental combustion analysis. Characteristic absorption features associated with NH4 can be seen in the reflectance spectra at wavelengths as short as ∼1 μm. In the near-infrared region, the most prominent absorption bands are located near 1.6, 2.0, and 2.2 μm. Absorption features characteristic of NH4+ occurred at slightly longer wavelengths in the mineral-bound NH4+ spectra than for free NH4+ for most of the samples. Differences in wavelength position are attributable to various factors, including differences in the type and polarizability of the anion(s) attached to the NH4+, degree and type of hydrogen bonding, molecule symmetry, and cation substitutions. Multiple absorption features, usually three absorption bands, in the mid-infrared region between ∼2.8 and 3.8 μm were seen in all but the most NH4-poor sample spectra, and are attributed to fundamentals, combinations, and overtones of stretching and bending vibrations of the NH4+ molecule. These features appear even in reflectance spectra of water-rich samples which exhibit a strong 3 μm region water absorption feature. While many of the samples examined in this study have NH4 absorption bands at unique wavelength positions, in order to discriminate between different NH4+-bearing phases, absorption features corresponding to molecules other than NH4+ should be included in spectral analysis. A qualitative comparison of the laboratory results to telescopic spectra of Asteroids 1 Ceres, 10 Hygiea, and 324 Bamberga for the 3 μm region demonstrates that a number of NH4-bearing phases are consistent with the observational data in terms of exhibiting an absorption band in the 3.07 μm region.

Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery

USGS Publications Warehouse

Rand, R.S.; Clark, R.N.; Livo, K.E.

2011-01-01

The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed.

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

NASA Technical Reports Server (NTRS)

Srivastava, Askok N.; Matthews, Bryan; Das, Santanu

2008-01-01

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Mineralogy of Mare Serenitatis on the near side of the Moon based on Chandrayaan-1 Moon Mineralogy Mapper (M3) observations

NASA Astrophysics Data System (ADS)

Kaur, Prabhjot; Bhattacharya, Satadru; Chauhan, Prakash; Ajai; Kiran Kumar, A. S.

2013-01-01

Spectral analysis of Mare Serenitatis has been carried out using Chandrayaan-1 Moon Mineralogy Mapper (M3) data in order to map the compositional diversity of the basaltic units that exist in the basin. Mare Serenitatis is characterized by multiple basaltic flows of different ages indicating a prolonged volcanism subsequent to the basin formation event. Reflectance spectra of fresh craters from the Mare Serenitatis have been analyzed to study the nature and location of the spectral absorption features around 1- and 2-μm respectively, arising due to the electronic charge transition of Fe2+ in the crystal lattice of pyroxenes and/or olivine. Chandrayaan-1 M3 data have been utilized to obtain an Integrated Band Depth (IBD) mosaic of the Serenitatis basin. Based on the spectral variations observed in the IBD mosaic, 13 spectral units have been mapped in the Mare Serenitatis. In the present study, we have also derived spectral band parameters, namely, band center, band strength, band area and band area ratio from the M3 data to study the mineralogical and compositional variations amongst the basaltic units of the studied basin. On the basis of spectral band parameter analysis, the pyroxene compositions of the basaltic units have been determined, which vary from low to intermediate end of the high-Ca pyroxene and probably represent a sub-calcic to calcic augite compositional range. Detailed spectral analyses reveal little variations in the mafic mineralogy of the mare basalts in terms of pyroxene chemistry. The uniformity in pyroxene composition across the basaltic units of Mare Serenitatis, therefore, suggest a probably stable basaltic source region, which might not have experienced large-scale fractionation during the prolonged volcanism that resulted in filling of the large Serenitatis basin.

Separable spectro-temporal Gabor filter bank features: Reducing the complexity of robust features for automatic speech recognition.

PubMed

Schädler, Marc René; Kollmeier, Birger

2015-04-01

To test if simultaneous spectral and temporal processing is required to extract robust features for automatic speech recognition (ASR), the robust spectro-temporal two-dimensional-Gabor filter bank (GBFB) front-end from Schädler, Meyer, and Kollmeier [J. Acoust. Soc. Am. 131, 4134-4151 (2012)] was de-composed into a spectral one-dimensional-Gabor filter bank and a temporal one-dimensional-Gabor filter bank. A feature set that is extracted with these separate spectral and temporal modulation filter banks was introduced, the separate Gabor filter bank (SGBFB) features, and evaluated on the CHiME (Computational Hearing in Multisource Environments) keywords-in-noise recognition task. From the perspective of robust ASR, the results showed that spectral and temporal processing can be performed independently and are not required to interact with each other. Using SGBFB features permitted the signal-to-noise ratio (SNR) to be lowered by 1.2 dB while still performing as well as the GBFB-based reference system, which corresponds to a relative improvement of the word error rate by 12.8%. Additionally, the real time factor of the spectro-temporal processing could be reduced by more than an order of magnitude. Compared to human listeners, the SNR needed to be 13 dB higher when using Mel-frequency cepstral coefficient features, 11 dB higher when using GBFB features, and 9 dB higher when using SGBFB features to achieve the same recognition performance.

Automated classification and visualization of healthy and pathological dental tissues based on near-infrared hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Usenik, Peter; Bürmen, Miran; Vrtovec, Tomaž; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan

2011-03-01

Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots which are difficult to diagnose. If detected early enough, such demineralization can be arrested and reversed by non-surgical means through well established dental treatments (fluoride therapy, anti-bacterial therapy, low intensity laser irradiation). Near-infrared (NIR) hyper-spectral imaging is a new promising technique for early detection of demineralization based on distinct spectral features of healthy and pathological dental tissues. In this study, we apply NIR hyper-spectral imaging to classify and visualize healthy and pathological dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized areas. For this purpose, a standardized teeth database was constructed consisting of 12 extracted human teeth with different degrees of natural dental lesions imaged by NIR hyper-spectral system, X-ray and digital color camera. The color and X-ray images of teeth were presented to a clinical expert for localization and classification of the dental tissues, thereby obtaining the gold standard. Principal component analysis was used for multivariate local modeling of healthy and pathological dental tissues. Finally, the dental tissues were classified by employing multiple discriminant analysis. High agreement was observed between the resulting classification and the gold standard with the classification sensitivity and specificity exceeding 85 % and 97 %, respectively. This study demonstrates that NIR hyper-spectral imaging has considerable diagnostic potential for imaging hard dental tissues.

Crystalline sulfur dioxide: Crystal field splittings, absolute band intensities and complex refractive indices derived from infrared spectra

NASA Technical Reports Server (NTRS)

Khanna, R. K.; Zhao, Guizhi

1986-01-01

The infrared absorption spectra of thin crystalline films of sulfur dioxide at 90 K are reported in the 2700 to 450/cm region. The observed multiplicity of the spectral features in the regions of fundamentals is attributed to factor group splittings of the modes in a biaxial crystal lattice and the naturally present minor S-34, S-36, and O-18 isotopic species. Complex refractive indices determined by an iterative Kramers-Kronig analysis of the extinction data, and absolute band strengths derived from them, are also reported in this region.

High Definition Confocal Imaging Modalities for the Characterization of Tissue-Engineered Substitutes.

PubMed

Mayrand, Dominique; Fradette, Julie

2018-01-01

Optimal imaging methods are necessary in order to perform a detailed characterization of thick tissue samples from either native or engineered tissues. Tissue-engineered substitutes are featuring increasing complexity including multiple cell types and capillary-like networks. Therefore, technical approaches allowing the visualization of the inner structural organization and cellular composition of tissues are needed. This chapter describes an optical clearing technique which facilitates the detailed characterization of whole-mount samples from skin and adipose tissues (ex vivo tissues and in vitro tissue-engineered substitutes) when combined with spectral confocal microscopy and quantitative analysis on image renderings.

Spectral properties near the Mott transition in the two-dimensional t-J model with next-nearest-neighbor hopping

NASA Astrophysics Data System (ADS)

Kohno, Masanori

2018-05-01

The single-particle spectral properties of the two-dimensional t-J model with next-nearest-neighbor hopping are investigated near the Mott transition by using cluster perturbation theory. The spectral features are interpreted by considering the effects of the next-nearest-neighbor hopping on the shift of the spectral-weight distribution of the two-dimensional t-J model. Various anomalous features observed in hole-doped and electron-doped high-temperature cuprate superconductors are collectively explained in the two-dimensional t-J model with next-nearest-neighbor hopping near the Mott transition.

Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China.

PubMed

Yue, Yuemin; Wang, Kelin; Zhang, Bing; Chen, Zhengchao; Jiao, Quanjun; Liu, Bo; Chen, Hongsong

2010-01-01

Remote sensing of local environmental conditions is not accessible if substrates are covered with vegetation. This study explored the relationship between vegetation spectra and karst eco-geo-environmental conditions. Hyperspectral remote sensing techniques showed that there were significant differences between spectral features of vegetation mainly distributed in karst and non-karst regions, and combination of 1,300- to 2,500-nm reflectance and 400- to 680-nm first-derivative spectra could delineate karst and non-karst vegetation groups. Canonical correspondence analysis (CCA) successfully assessed to what extent the variation of vegetation spectral features can be explained by associated eco-geo-environmental variables, and it was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst region. Our study indicates that vegetation spectra is tightly linked to eco-geo-environmental conditions and CCA is an effective means of studying the relationship between vegetation spectral features and eco-geo-environmental variables. Employing a combination of spectral and spatial analysis, it is anticipated that hyperspectral imagery can be used in interpreting or mapping eco-geo-environmental conditions covered with vegetation in karst region.

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

Selected issues connected with determination of requirements of spectral properties of camouflage patterns

NASA Astrophysics Data System (ADS)

Racek, František; Jobánek, Adam; Baláž, Teodor; Krejčí, Jaroslav

2017-10-01

Traditionally spectral reflectance of the material is measured and compared with permitted spectral reflectance boundaries. The boundaries are limited by upper and lower curve of spectral reflectance. The boundaries for unique color has to fulfil the operational requirements as a versatility of utilization through the all year seasons, day and weather condition on one hand and chromatic and spectral matching with background as well as the manufacturability on the other hand. The interval between the boundaries suffers with ambivalent feature. Camouflage pattern producer would be happy to see it much wider, but blending effect into its particular background could be better with narrower tolerance limits. From the point of view of long time user of camouflage pattern battledress, there seems to be another ambivalent feature. Width of the tolerance zone reflecting natural dispersion of spectral reflectance values allows the significant distortions of shape of the spectral curve inside the given boundaries.

Intrinsic fluorescence excitation-emission matrix spectral features of cottonseed protein fractions and the effects of denaturants

USDA-ARS?s Scientific Manuscript database

To better understand the functional and physicochemical properties of cottonseed protein, we investigated the intrinsic fluorescence excitation-emission matrix (EEM) spectral features of cottonseed protein isolate (CSPI) and sequentially extracted water (CSPw) and alkali (CSPa) protein fractions, an...

Side information in coded aperture compressive spectral imaging

NASA Astrophysics Data System (ADS)

Galvis, Laura; Arguello, Henry; Lau, Daniel; Arce, Gonzalo R.

2017-02-01

Coded aperture compressive spectral imagers sense a three-dimensional cube by using two-dimensional projections of the coded and spectrally dispersed source. These imagers systems often rely on FPA detectors, SLMs, micromirror devices (DMDs), and dispersive elements. The use of the DMDs to implement the coded apertures facilitates the capture of multiple projections, each admitting a different coded aperture pattern. The DMD allows not only to collect the sufficient number of measurements for spectrally rich scenes or very detailed spatial scenes but to design the spatial structure of the coded apertures to maximize the information content on the compressive measurements. Although sparsity is the only signal characteristic usually assumed for reconstruction in compressing sensing, other forms of prior information such as side information have been included as a way to improve the quality of the reconstructions. This paper presents the coded aperture design in a compressive spectral imager with side information in the form of RGB images of the scene. The use of RGB images as side information of the compressive sensing architecture has two main advantages: the RGB is not only used to improve the reconstruction quality but to optimally design the coded apertures for the sensing process. The coded aperture design is based on the RGB scene and thus the coded aperture structure exploits key features such as scene edges. Real reconstructions of noisy compressed measurements demonstrate the benefit of the designed coded apertures in addition to the improvement in the reconstruction quality obtained by the use of side information.

Use of spectral analogy to evaluate canopy reflectance sensitivity to leaf optical property

NASA Technical Reports Server (NTRS)

Baret, Frederic; Vanderbilt, Vern C.; Steven, Michael D.; Jacquemoud, Stephane

1993-01-01

The spectral variation of canopy reflectance is mostly governed by the absorption properties of the elements, hence the leaves, since their intrinsic scattering properties show very little spectral variation. The relationship between canopy reflectance and leaf reflectance measured at the red edge over sugar beet canopies was used to simulate canopy reflectance from leaf reflectance spectra measured over the whole spectral domain. The results show that the spectral analogies found allows accurate reconstruction of canopy reflectance spectra. Explicit assumptions about the very low spectral variation of leaf intrinsic scattering properties are thus indirectly justified. The sensitivity of canopy reflectance (rho(sub c)) to leaf optical properties can then be investigated from concurrent spectral variations of canopy (delta rho(sub c)/delta lambda) and leaf reflectance (delta rho(sub l)/delta lambda): (delta rho(sub c))/(delta rho(sub l)) = ((delta rho(sub c))/(delta lambda) ((delta rho( sub l))/(delta lambda))(sup -1)). This expression is strictly valid only when the optical properties of the soil background or the other vegetation elements such as bark are either spectrally flat or do not contribute significantly to canopy reflectance. Simulations using the SAIL and PROSPECT models demonstrate that the sensitivity of canopy reflectance to leaf reflectance is significant for large vegetation cover fractions in spectral domains where absorption is low. In these conditions, multiple, scattering enhances the leaf absorption features by a factor that can be greater than 2.0. To override the limitations of the SAIL model for the description of the canopy architecture, we tested the previous findings on experimental data. Concurrent canopy and leaf reflectance spectra were measured for a range of sugar beet canopies. The results show good agreement with the theoretical findings. Conclusions are drawn about the applicability of these findings, with particular attention to the potential detectability of leaf biochemical composition from canopy reflectance sensed from space.

Common Prairie feeds with different soluble and insoluble fractions used for CPM diet formulation in dairy cattle: impact of carbohydrate-protein matrix structure on protein and other primary nutrient digestion.

PubMed

Peng, Quanhui; Wang, Zhisheng; Zhang, Xuewei; Yu, Peiqiang

2014-01-01

An experiment was conducted to investigate the relationship of carbohydrates molecular spectral characteristics to rumen degradability of primary nutrients in Prairie feeds in dairy cattle. In total, 12 different types of feeds were selected, each type of feed was from three different source with total 37 samples. Six types of them were energy-sourced feeds and the others were protein-sourced feeds. The carbohydrates molecular spectral intensity of various functional groups were collected using Fourier transform infrared attenuated total reflectance (ATR-FT/IR) spectroscopy. In the in situ study, the results showed that the rumen digestibility and digestible fractions of primary nutrients (DM, OM, NCP, and CP) were significantly different (P<0.05) among the feeds. The spectral bands features were significantly different (P<0.05) among the feeds. Spectral intensities of A_Cell, H_1415 and H_1370 were weakly positively correlated with in situ rumen digestibility and digestible fractions of DM, OM and NCP. Spectral intensities of H_1150, H_1015, A_1, and A_3 were weakly negatively associated with in situ rumen degradation of CP. Spectral intensities of A_1240 and H_1240, mainly associated with cellulosic compounds, were correlated with rumen CP degradation. The multiple regression analysis demonstrated that the spectral intensities of A_3 and H_1415 played the most important role and could be used as a potential tool to predict rumen protein degradation of feeds in dairy cattle. In conclusion, this study showed that the carbohydrates as a whole have an effect on protein rumen degradation, rather than cellulose alone, indicating carbohydrate-protein matrix structure impact protein utilization in dairy cattle. The non-invasive molecular spectral technique (ATR-FT/IR) could be used as a rapid potential tool to predict rumen protein degradation of feedstuffs by using molecular spectral bands intensities in carbohydrate fingerprint region. Copyright © 2013 Elsevier B.V. All rights reserved.

Common Prairie feeds with different soluble and insoluble fractions used for CPM diet formulation in dairy cattle: Impact of carbohydrate-protein matrix structure on protein and other primary nutrient digestion

NASA Astrophysics Data System (ADS)

Peng, Quanhui; Wang, Zhisheng; Zhang, Xuewei; Yu, Peiqiang

2014-03-01

An experiment was conducted to investigate the relationship of carbohydrates molecular spectral characteristics to rumen degradability of primary nutrients in Prairie feeds in dairy cattle. In total, 12 different types of feeds were selected, each type of feed was from three different source with total 37 samples. Six types of them were energy-sourced feeds and the others were protein-sourced feeds. The carbohydrates molecular spectral intensity of various functional groups were collected using Fourier transform infrared attenuated total reflectance (ATR-FT/IR) spectroscopy. In the in situ study, the results showed that the rumen digestibility and digestible fractions of primary nutrients (DM, OM, NCP, and CP) were significantly different (P < 0.05) among the feeds. The spectral bands features were significantly different (P < 0.05) among the feeds. Spectral intensities of A_Cell, H_1415 and H_1370 were weakly positively correlated with in situ rumen digestibility and digestible fractions of DM, OM and NCP. Spectral intensities of H_1150, H_1015, A_1, and A_3 were weakly negatively associated with in situ rumen degradation of CP. Spectral intensities of A_1240 and H_1240, mainly associated with cellulosic compounds, were correlated with rumen CP degradation. The multiple regression analysis demonstrated that the spectral intensities of A_3 and H_1415 played the most important role and could be used as a potential tool to predict rumen protein degradation of feeds in dairy cattle. In conclusion, this study showed that the carbohydrates as a whole have an effect on protein rumen degradation, rather than cellulose alone, indicating carbohydrate-protein matrix structure impact protein utilization in dairy cattle. The non-invasive molecular spectral technique (ATR-FT/IR) could be used as a rapid potential tool to predict rumen protein degradation of feedstuffs by using molecular spectral bands intensities in carbohydrate fingerprint region.

Hyperspectral feature mapping classification based on mathematical morphology

NASA Astrophysics Data System (ADS)

Liu, Chang; Li, Junwei; Wang, Guangping; Wu, Jingli

2016-03-01

This paper proposed a hyperspectral feature mapping classification algorithm based on mathematical morphology. Without the priori information such as spectral library etc., the spectral and spatial information can be used to realize the hyperspectral feature mapping classification. The mathematical morphological erosion and dilation operations are performed respectively to extract endmembers. The spectral feature mapping algorithm is used to carry on hyperspectral image classification. The hyperspectral image collected by AVIRIS is applied to evaluate the proposed algorithm. The proposed algorithm is compared with minimum Euclidean distance mapping algorithm, minimum Mahalanobis distance mapping algorithm, SAM algorithm and binary encoding mapping algorithm. From the results of the experiments, it is illuminated that the proposed algorithm's performance is better than that of the other algorithms under the same condition and has higher classification accuracy.

O2 on ganymede: Spectral characteristics and plasma formation mechanisms

USGS Publications Warehouse

Calvin, W.M.; Johnson, R.E.; Spencer, J.R.

1996-01-01

Weak absorption features in the visible reflectance spectrum of Jupiter's satellite Ganymede have been correlated to those observed in the spectrum of molecular oxygen. We examine the spectral characteristics of these absorption features in all phases of O2 and conclude that the molecular oxygen is most likely present at densities similar to the liquid or solid ??-phase. The contribution of O2 to spectral features observed on Ganymede in the near-infrared wavelength region affects the previous estimates of photon pathlength in ice. The concentration of the visible absorption features on the trailing hemisphere of Ganymede suggests an origin due to bombardment by magneto-spheric ions. We derive an approximate O2 formation rate from this mechanism and consider the state of O2 within the surface.

Using the Properties of Broad Absorption Line Quasars to Illuminate Quasar Structure

NASA Astrophysics Data System (ADS)

Yong, Suk Yee; King, Anthea L.; Webster, Rachel L.; Bate, Nicholas F.; O'Dowd, Matthew J.; Labrie, Kathleen

2018-06-01

A key to understanding quasar unification paradigms is the emission properties of broad absorption line quasars (BALQs). The fact that only a small fraction of quasar spectra exhibit deep absorption troughs blueward of the broad permitted emission lines provides a crucial clue to the structure of quasar emitting regions. To learn whether it is possible to discriminate between the BALQ and non-BALQ populations given the observed spectral properties of a quasar, we employ two approaches: one based on statistical methods and the other supervised machine learning classification, applied to quasar samples from the Sloan Digital Sky Survey. The features explored include continuum and emission line properties, in particular the absolute magnitude, redshift, spectral index, line width, asymmetry, strength, and relative velocity offsets of high-ionisation C IV λ1549 and low-ionisation Mg II λ2798 lines. We consider a complete population of quasars, and assume that the statistical distributions of properties represent all angles where the quasar is viewed without obscuration. The distributions of the BALQ and non-BALQ sample properties show few significant differences. None of the observed continuum and emission line features are capable of differentiating between the two samples. Most published narrow disk-wind models are inconsistent with these observations, and an alternative disk-wind model is proposed. The key feature of the proposed model is a disk-wind filling a wide opening angle with multiple radial streams of dense clumps.

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Akbari, D.

2017-11-01

In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

A method for fast selecting feature wavelengths from the spectral information of crop nitrogen

USDA-ARS?s Scientific Manuscript database

Research on a method for fast selecting feature wavelengths from the nitrogen spectral information is necessary, which can determine the nitrogen content of crops. Based on the uniformity of uniform design, this paper proposed an improved particle swarm optimization (PSO) method. The method can ch...

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis

NASA Astrophysics Data System (ADS)

Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier

2012-11-01

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.

Automatic classification of retinal three-dimensional optical coherence tomography images using principal component analysis network with composite kernels.

PubMed

Fang, Leyuan; Wang, Chong; Li, Shutao; Yan, Jun; Chen, Xiangdong; Rabbani, Hossein

2017-11-01

We present an automatic method, termed as the principal component analysis network with composite kernel (PCANet-CK), for the classification of three-dimensional (3-D) retinal optical coherence tomography (OCT) images. Specifically, the proposed PCANet-CK method first utilizes the PCANet to automatically learn features from each B-scan of the 3-D retinal OCT images. Then, multiple kernels are separately applied to a set of very important features of the B-scans and these kernels are fused together, which can jointly exploit the correlations among features of the 3-D OCT images. Finally, the fused (composite) kernel is incorporated into an extreme learning machine for the OCT image classification. We tested our proposed algorithm on two real 3-D spectral domain OCT (SD-OCT) datasets (of normal subjects and subjects with the macular edema and age-related macular degeneration), which demonstrated its effectiveness. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

WAVELENGTH AND ALIGNMENT TESTS FOR CONFOCAL SPECTRAL IMAGING SYSTEMS

EPA Science Inventory

Confocal spectral imaging (CSI) microscope systems now on the market delineate multiple fluorescent proteins, labels, or dyes within biological specimens by performing spectral characterizations. However, we find that some CSI present inconsistent spectral profiles of reference s...

Matrix Methods for Estimating the Coherence Functions from Estimates of the Cross-Spectral Density Matrix

DOE PAGES

Smallwood, D. O.

1996-01-01

It is shown that the usual method for estimating the coherence functions (ordinary, partial, and multiple) for a general multiple-input! multiple-output problem can be expressed as a modified form of Cholesky decomposition of the cross-spectral density matrix of the input and output records. The results can be equivalently obtained using singular value decomposition (SVD) of the cross-spectral density matrix. Using SVD suggests a new form of fractional coherence. The formulation as a SVD problem also suggests a way to order the inputs when a natural physical order of the inputs is absent.

Analysis of Specular Reflections Off Geostationary Satellites

NASA Astrophysics Data System (ADS)

Jolley, A.

2016-09-01

Many photometric studies of artificial satellites have attempted to define procedures that minimise the size of datasets required to infer information about satellites. However, it is unclear whether deliberately limiting the size of datasets significantly reduces the potential for information to be derived from them. In 2013 an experiment was conducted using a 14 inch Celestron CG-14 telescope to gain multiple night-long, high temporal resolution datasets of six geostationary satellites [1]. This experiment produced evidence of complex variations in the spectral energy distribution (SED) of reflections off satellite surface materials, particularly during specular reflections. Importantly, specific features relating to the SED variations could only be detected with high temporal resolution data. An update is provided regarding the nature of SED and colour variations during specular reflections, including how some of the variables involved contribute to these variations. Results show that care must be taken when comparing observed spectra to a spectral library for the purpose of material identification; a spectral library that uses wavelength as the only variable will be unable to capture changes that occur to a material's reflected spectra with changing illumination and observation geometry. Conversely, colour variations with changing illumination and observation geometry might provide an alternative means of determining material types.

Lithologic mapping of the Mordor, NT, Australia ultramafic complex by using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

USGS Publications Warehouse

Rowan, L.C.; Mars, J.C.; Simpson, C.J.

2005-01-01

Spectral measurements made in the Mordor Pound, NT, Australia study area using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), in the laboratory and in situ show dominantly Al-OH and ferric-iron VNIR-SWIR absorption features in felsic rock spectra and ferrous-iron and Fe,Mg-OH features in the mafic-ultramafic rock spectra. ASTER ratio images, matched-filter, and spectral-angle mapper processing (SAM) were evaluated for mapping the lithologies. Matched-filter processing in which VNIR + SWIR image spectra were used for reference resulted in 4 felsic classes and 4 mafic-ultramafic classes based on Al-OH or Fe,Mg-OH absorption features and, in some, subtle reflectance differences related to differential weathering and vegetation. These results were similar to those obtained by match-filter analysis of HyMap data from a previous study, but the units were more clearly demarcated in the HyMap image. ASTER TIR spectral emittance data and laboratory emissivity measurements document a wide wavelength range of Si-O spectral features, which reflect the lithological diversity of the Mordor ultramafic complex and adjacent rocks. SAM processing of the spectral emittance data distinguished 2 classes representing the mafic-ultramafic rocks and 4 classes comprising the quartzose to intermediate composition rocks. Utilization of the complementary attributes of the spectral reflectance and spectral emittance data resulted in discrimination of 4 mafic-ultramafic categories; 3 categories of alluvial-colluvial deposits; and a significantly more completely mapped quartzite unit than could be accomplished by using either data set alone. ?? 2005 Elsevier Inc. All rights reserved.

Observations and Numerical Modeling of the Jovian Ribbon

NASA Technical Reports Server (NTRS)

Cosentino, R. G.; Simon, A.; Morales-Juberias, R.; Sayanagi, K. M.

2015-01-01

Multiple wavelength observations made by the Hubble Space Telescope in early 2007 show the presence of a wavy, high-contrast feature in Jupiter's atmosphere near 30 degrees North. The "Jovian Ribbon," best seen at 410 nanometers, irregularly undulates in latitude and is time-variable in appearance. A meridional intensity gradient algorithm was applied to the observations to track the Ribbon's contour. Spectral analysis of the contour revealed that the Ribbon's structure is a combination of several wavenumbers ranging from k equals 8-40. The Ribbon is a dynamic structure that has been observed to have spectral power for dominant wavenumbers which vary over a time period of one month. The presence of the Ribbon correlates with periods when the velocity of the westward jet at the same location is highest. We conducted numerical simulations to investigate the stability of westward jets of varying speed, vertical shear, and background static stability to different perturbations. A Ribbon-like morphology was best reproduced with a 35 per millisecond westward jet that decreases in amplitude for pressures greater than 700 hectopascals and a background static stability of N equals 0.005 per second perturbed by heat pulses constrained to latitudes south of 30 degrees North. Additionally, the simulated feature had wavenumbers that qualitatively matched observations and evolved throughout the simulation reproducing the Jovian Ribbon's dynamic structure.

Bipolar gas outflow from the nova V458 Vul

NASA Astrophysics Data System (ADS)

Goranskij, V. P.; Barsukova, E. A.; Fatkhullin, T. A.

2010-06-01

Classical nova V458 Vul (N Vul 2007 No.1) was detected as a supersoft X-ray source by the Swift XRT (ATel#1246, #1603). This star is interesting with its spectral class change: features of Fe II class nova completely changed by features of He/N class in the SSS phase (T.N. Tarasova, IBVS No.5807). We performed spectral observations of V458 Vul with the Russian 6-m telescope BTA and spectral camera SCORPIO on 2010 June 9.84 UT.

Surface materials map of Afghanistan: carbonates, phyllosilicates, sulfates, altered minerals, and other materials

USGS Publications Warehouse

Kokaly, Raymond F.; King, Trude V.V.; Hoefen, Todd M.; Dudek, Kathleen B.; Livo, Keith E.

2012-01-01

This map shows the distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of HyMap imaging spectrometer data of Afghanistan. Using a NASA (National Aeronautics and Space Administration) WB-57 aircraft flown at an altitude of ~15,240 meters or ~50,000 feet, 218 flight lines of data were collected over Afghanistan between August 22 and October 2, 2007. The HyMap data were converted to apparent surface reflectance, then further empirically adjusted using ground-based reflectance measurements. The reflectance spectrum of each pixel of HyMap data was compared to the spectral features of reference entries in a spectral library of minerals, vegetation, water, ice, and snow. This map shows the spatial distribution of minerals that have diagnostic absorption features in the shortwave infrared wavelengths. These absorption features result primarily from characteristic chemical bonds and mineralogical vibrations. Several criteria, including (1) the reliability of detection and discrimination of minerals using the HyMap spectrometer data, (2) the relative abundance of minerals, and (3) the importance of particular minerals to studies of Afghanistan's natural resources, guided the selection of entries in the reference spectral library and, therefore, guided the selection of mineral classes shown on this map. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having similar spectral features were less easily discriminated, especially where the minerals were not particularly abundant and (or) where vegetation cover reduced the absorption strength of mineral features. Complications in reflectance calibration also affected the detection and identification of minerals.

Web Image Search Re-ranking with Click-based Similarity and Typicality.

PubMed

Yang, Xiaopeng; Mei, Tao; Zhang, Yong Dong; Liu, Jie; Satoh, Shin'ichi

2016-07-20

In image search re-ranking, besides the well known semantic gap, intent gap, which is the gap between the representation of users' query/demand and the real intent of the users, is becoming a major problem restricting the development of image retrieval. To reduce human effects, in this paper, we use image click-through data, which can be viewed as the "implicit feedback" from users, to help overcome the intention gap, and further improve the image search performance. Generally, the hypothesis visually similar images should be close in a ranking list and the strategy images with higher relevance should be ranked higher than others are widely accepted. To obtain satisfying search results, thus, image similarity and the level of relevance typicality are determinate factors correspondingly. However, when measuring image similarity and typicality, conventional re-ranking approaches only consider visual information and initial ranks of images, while overlooking the influence of click-through data. This paper presents a novel re-ranking approach, named spectral clustering re-ranking with click-based similarity and typicality (SCCST). First, to learn an appropriate similarity measurement, we propose click-based multi-feature similarity learning algorithm (CMSL), which conducts metric learning based on clickbased triplets selection, and integrates multiple features into a unified similarity space via multiple kernel learning. Then based on the learnt click-based image similarity measure, we conduct spectral clustering to group visually and semantically similar images into same clusters, and get the final re-rank list by calculating click-based clusters typicality and withinclusters click-based image typicality in descending order. Our experiments conducted on two real-world query-image datasets with diverse representative queries show that our proposed reranking approach can significantly improve initial search results, and outperform several existing re-ranking approaches.

Spectra of Particulate Backscattering in Natural Waters

NASA Technical Reports Server (NTRS)

Gordon, Howard, R.; Lewis, Marlon R.; McLean, Scott D.; Twardowski, Michael S.; Freeman, Scott A.; Voss, Kenneth J.; Boynton, Chris G.

2009-01-01

Hyperspectral profiles of downwelling irradiance and upwelling radiance in natural waters (oligotrophic and mesotrophic) are combined with inverse radiative transfer to obtain high resolution spectra of the absorption coefficient (a) and the backscattering coefficient (bb) of the water and its constituents. The absorption coefficient at the mesotrophic station clearly shows spectral absorption features attributable to several phytoplankton pigments (Chlorophyll a, b, c, and Carotenoids). The backscattering shows only weak spectral features and can be well represented by a power-law variation with wavelength (lambda): b(sub b) approx. Lambda(sup -n), where n is a constant between 0.4 and 1.0. However, the weak spectral features in b(sub b), suggest that it is depressed in spectral regions of strong particle absorption. The applicability of the present inverse radiative transfer algorithm, which omits the influence of Raman scattering, is limited to lambda < 490 nm in oligotrophic waters and lambda < 575 nm in mesotrophic waters.

SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

True color scanning laser ophthalmoscopy and optical coherence tomography handheld probe

PubMed Central

LaRocca, Francesco; Nankivil, Derek; Farsiu, Sina; Izatt, Joseph A.

2014-01-01

Scanning laser ophthalmoscopes (SLOs) are able to achieve superior contrast and axial sectioning capability compared to fundus photography. However, SLOs typically use monochromatic illumination and are thus unable to extract color information of the retina. Previous color SLO imaging techniques utilized multiple lasers or narrow band sources for illumination, which allowed for multiple color but not “true color” imaging as done in fundus photography. We describe the first “true color” SLO, handheld color SLO, and combined color SLO integrated with a spectral domain optical coherence tomography (OCT) system. To achieve accurate color imaging, the SLO was calibrated with a color test target and utilized an achromatizing lens when imaging the retina to correct for the eye’s longitudinal chromatic aberration. Color SLO and OCT images from volunteers were then acquired simultaneously with a combined power under the ANSI limit. Images from this system were then compared with those from commercially available SLOs featuring multiple narrow-band color imaging. PMID:25401032

A light-trapping strategy for nanocrystalline silicon thin-film solar cells using three-dimensionally assembled nanoparticle structures.

PubMed

Ha, Kyungyeon; Jang, Eunseok; Jang, Segeun; Lee, Jong-Kwon; Jang, Min Seok; Choi, Hoseop; Cho, Jun-Sik; Choi, Mansoo

2016-02-05

We report three-dimensionally assembled nanoparticle structures inducing multiple plasmon resonances for broadband light harvesting in nanocrystalline silicon (nc-Si:H) thin-film solar cells. A three-dimensional multiscale (3DM) assembly of nanoparticles generated using a multi-pin spark discharge method has been accomplished over a large area under atmospheric conditions via ion-assisted aerosol lithography. The multiscale features of the sophisticated 3DM structures exhibit surface plasmon resonances at multiple frequencies, which increase light scattering and absorption efficiency over a wide spectral range from 350-1100 nm. The multiple plasmon resonances, together with the antireflection functionality arising from the conformally deposited top surface of the 3D solar cell, lead to a 22% and an 11% improvement in power conversion efficiency of the nc-Si:H thin-film solar cells compared to flat cells and cells employing nanoparticle clusters, respectively. Finite-difference time-domain simulations were also carried out to confirm that the improved device performance mainly originates from the multiple plasmon resonances generated from three-dimensionally assembled nanoparticle structures.

Observations of discrete magnetosonic waves off the magnetic equator

DOE PAGES

Zhima, Zeren; Chen, Lunjin; Fu, Huishan; ...

2015-11-23

Fast mode magnetosonic waves are typically confined close to the magnetic equator and exhibit harmonic structures at multiples of the local, equatorial proton cyclotron frequency. Here, we report observations of magnetosonic waves well off the equator at geomagnetic latitudes from -16.5°to -17.9° and L shell ~2.7–4.6. The observed waves exhibit discrete spectral structures with multiple frequency spacings. The predominant frequency spacings are ~6 and 9 Hz, neither of which is equal to the local proton cyclotron frequency. Backward ray tracing simulations show that the feature of multiple frequency spacings is caused by propagation from two spatially narrow equatorial source regionsmore » located at L ≈ 4.2 and 3.7. The equatorial proton cyclotron frequencies at those two locations match the two observed frequency spacings. Finally, our analysis provides the first observations of the harmonic nature of magnetosonic waves well away from the equatorial region and suggests that the propagation from multiple equatorial sources contributes to these off-equatorial magnetosonic emissions with varying frequency spacings.« less

UTILIZATION OF FUNDUS AUTOFLUORESCENCE, SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY, AND ENHANCED DEPTH IMAGING IN THE CHARACTERIZATION OF BIETTI CRYSTALLINE DYSTROPHY IN DIFFERENT STAGES.

PubMed

Li, Qian; Li, Yang; Zhang, Xiaohui; Xu, Zhangxing; Zhu, Xiaoqing; Ma, Kai; She, Haicheng; Peng, Xiaoyan

2015-10-01

To characterize Bietti crystalline dystrophy (BCD) in different stages using multiple imaging modalities. Sixteen participants clinically diagnosed as BCD were included in the retrospective study and were categorized into 3 stages according to fundus photography. Eleven patients were genetically confirmed. Fundus autofluorescence, spectral domain optical coherence tomography, and enhanced depth imaging features of BCD were analyzed. On fundus autofluorescence, the abnormal autofluorescence was shown to enlarge in area and decrease in intensity with stages. Using spectral domain optical coherence tomography, the abnormalities in Stage 1 were observed to localize in outer retinal layers, whereas in Stage 2 and Stage 3, more extensive retinal atrophy was seen. In enhanced depth imaging, the subfoveal choroidal layers were delineated clearly in Stage 1; in Stage 2, destructions were primarily found in the choriocapillaris with associated alterations in the outer vessels; Stage 3 BCD displayed severe choroidal thinning. Choroidal neovascularization and macular edema were exhibited with high incidence. IVS6-8del17bp/inGC of the CYP4V2 gene was the most common mutant allele. Noninvasive fundus autofluorescence, spectral domain optical coherence tomography, and enhanced depth imaging may help to characterize the chorioretinal pathology of BCD at different degrees, and therefore, we propose staging of BCD depending on those methods. Physicians should be cautious of the vision-threatening complications of the disease.

Multispectral information for gas and aerosol retrieval from TANSO-FTS instrument

NASA Astrophysics Data System (ADS)

Herbin, H.; Labonnote, L. C.; Dubuisson, P.

2012-11-01

The Greenhouse gases Observing SATellite (GOSAT) mission and in particular TANSO-FTS instrument has the advantage to measure simultaneously the same field of view in different spectral ranges with a high spectral resolution. These features are promising to improve, not only, gaseous retrieval in clear sky or scattering atmosphere, but also to retrieve aerosol parameters. Therefore, this paper is dedicated to an Information Content (IC) analysis of potential synergy between thermal infrared, shortwave infrared and visible, in order to obtain a more accurate retrieval of gas and aerosol. The latter is based on Shannon theory and used a sophisticated radiative transfer algorithm developed at "Laboratoire d'Optique Atmosphérique", dealing with multiple scattering. This forward model can be relied to an optimal estimation method, which allows simultaneously retrieving gases profiles and aerosol granulometry and concentration. The analysis of the information provided by the spectral synergy is based on climatology of dust, volcanic ash and biomass burning aerosols. This work was conducted in order to develop a powerful tool that allows retrieving simultaneously not only the gas concentrations but also the aerosol characteristics by selecting the so called "best channels", i.e. the channels that bring most of the information concerning gas and aerosol. The methodology developed in this paper could also be used to define the specifications of future high spectral resolution mission to reach a given accuracy on retrieved parameters.

Development and analysis of spectroscopic learning tools and the light and spectroscopy concept inventory for introductory college astronomy

NASA Astrophysics Data System (ADS)

Bardar, Erin M.

Electromagnetic radiation is the fundamental carrier of astronomical information. Spectral features serve as the fingerprints of the universe, revealing many important properties of objects in the cosmos such as temperature, elemental compositions, and relative motion. Because of its importance to astronomical research, the nature of light and the electromagnetic spectrum is by far the most universally covered topic in astronomy education. Yet, to the surprise and disappointment of instructors, many students struggle to understand underlying fundamental concepts related to light and spectroscopic phenomena. This dissertation describes research into introductory college astronomy students' understanding of light and spectroscopy concepts, through the development and analysis of both instructional materials and an assessment instrument. The purpose of this research was two-fold: (1) to develop a novel suite of spectroscopic learning tools that enhance student understanding of light and spectroscopy and (2) to design and validate a Light and Spectroscopy Concept Inventory (LSCI) with the sensitivity to distinguish the relative effectiveness of various teaching interventions within the context of introductory college astronomy. Through a systematic investigation that included multiple rounds of clinical interviews, open-ended written surveys, and multiple-choice testing, introductory college astronomy students' commonly held misconceptions and reasoning difficulties were explored for concepts relating to: (1) The nature of the electromagnetic spectrum, including the interrelationships of wavelength, frequency, energy, and speed; (2) interpretation of Doppler shift; (3) properties of blackbody radiation; and (4) the connection between spectral features and underlying physical processes. These difficulties guided the development of instructional materials including six unique "homelab" exercises, a binocular spectrometer, a spectral analysis software tool, and the 26-question Light and Spectroscopy Concept Inventory (LSCI). In the fall of 2005, a multi-institution field-test of the LSCI was conducted with student examinees from 14 course sections at 11 colleges and universities employing various instructional techniques. Through statistical analysis, the inventory was proven to be a reliable (Cronbach's alpha = 0.77) and valid assessment instrument that was able to illustrate statistically significant learning gains (p < 0.05) for most course sections, with students utilizing our suite of instructional materials exhibiting among the highest performance gains (Effect Size = 1.31).

IRAS Low Resolution Spectra of Asteroids

NASA Technical Reports Server (NTRS)

Cohen, Martin; Walker, Russell G.

2002-01-01

Optical/near-infrared studies of asteroids are based on reflected sunlight and surface albedo variations create broad spectral features, suggestive of families of materials. There is a significant literature on these features, but there is very little work in the thermal infrared that directly probes the materials emitting on the surfaces of asteroids. We have searched for and extracted 534 thermal spectra of 245 asteroids from the original Dutch (Groningen) archive of spectra observed by the IRAS Low Resolution Spectrometer (LRS). We find that, in general, the observed shapes of the spectral continua are inconsistent with that predicted by the standard thermal model used by IRAS. Thermal models such as proposed by Harris (1998) and Harris et al.(1998) for the near-earth asteroids with the "beaming parameter" in the range of 1.0 to 1.2 best represent the observed spectral shapes. This implies that the IRAS Minor Planet Survey (IMPS, Tedesco, 1992) and the Supplementary IMPS (SIMPS, Tedesco, et al., 2002) derived asteroid diameters are systematically underestimated, and the albedos are overestimated. We have tentatively identified several spectral features that appear to be diagnostic of at least families of materials. The variation of spectral features with taxonomic class hints that thermal infrared spectra can be a valuable tool for taxonomic classification of asteroids.

Probing collective oscillation of d-orbital electrons at the nanoscale

NASA Astrophysics Data System (ADS)

Dhall, Rohan; Vigil-Fowler, Derek; Houston Dycus, J.; Kirste, Ronny; Mita, Seiji; Sitar, Zlatko; Collazo, Ramon; LeBeau, James M.

2018-02-01

Here, we demonstrate that high energy electrons can be used to explore the collective oscillation of s, p, and d orbital electrons at the nanometer length scale. Using epitaxial AlGaN/AlN quantum wells as a test system, we observe the emergence of additional features in the loss spectrum with the increasing Ga content. A comparison of the observed spectra with ab-initio theory reveals that the origin of these spectral features lies in excitations of 3d-electrons contributed by Ga. We find that these modes differ in energy from the valence electron plasmons in Al1-xGaxN due to the different polarizabilities of the d electrons. Finally, we study the dependence of observed spectral features on the Ga content, lending insights into the origin of these spectral features, and their coupling with electron-hole excitations.

Modification of spectral features by nonhuman primates

PubMed Central

Weiss, Daniel J.; Hotchkin, Cara F.; Parks, Susan E.

2017-01-01

Ackermann et al. discuss the lack of evidence for vocal control in nonhuman primates. We suggest that nonhuman primates may be capable of achieving greater vocal control than previously supposed. In support of this assertion, we discuss new evidence that nonhuman primates are capable of modifying spectral features in their vocalizations. PMID:25514964

Analysis of substrate and plant spectral features of semi-arid shrub communities in the Owens Valley, California

NASA Technical Reports Server (NTRS)

Ustin, S. L.; Rock, B. N.; Woodward, R. A.

1986-01-01

Airborne Imaging Spectrometer (AIS) data were analyzed to deduce plant density and species composition in three semi-arid shrub-dominated communities of Owens Valley, CA, occurring on either a sand, granite alluvium, or basalt substrate. The high-spectral resolution AIS data were related to spectra obtained with field portable spectrometers, which in turn were related to plant and soil characteristics of the communities. Many of the dominant species have unique spectral features which permit their identification in AIS pixel images. The canopy-induced shadow may be a major factor influencing substrate spectral properties during fall and winter, because of low sun angles. Moreover, changes in spectral signatures following dormancy and leaf senescence tend to decrease contrasts between the plant community and the geologic substrate, also suggesting that fall and winter are a difficult time of year for spectral analyses.

Design of a multi-spectral imager built using the compressive sensing single-pixel camera architecture

NASA Astrophysics Data System (ADS)

McMackin, Lenore; Herman, Matthew A.; Weston, Tyler

2016-02-01

We present the design of a multi-spectral imager built using the architecture of the single-pixel camera. The architecture is enabled by the novel sampling theory of compressive sensing implemented optically using the Texas Instruments DLP™ micro-mirror array. The array not only implements spatial modulation necessary for compressive imaging but also provides unique diffractive spectral features that result in a multi-spectral, high-spatial resolution imager design. The new camera design provides multi-spectral imagery in a wavelength range that extends from the visible to the shortwave infrared without reduction in spatial resolution. In addition to the compressive imaging spectrometer design, we present a diffractive model of the architecture that allows us to predict a variety of detailed functional spatial and spectral design features. We present modeling results, architectural design and experimental results that prove the concept.

Identification of Fourier transform infrared photoacoustic spectral features for detection of Aspergillus flavus infection in corn.

PubMed

Gordon, S H; Schudy, R B; Wheeler, B C; Wicklow, D T; Greene, R V

1997-04-01

Aspergillus flavus and other pathogenic fungi display typical infrared spectra which differ significantly from spectra of substrate materials such as corn. On this basis, specific spectral features have been identified which permit detection of fungal infection on the surface of corn kernels by photoacoustic infrared spectroscopy. In a blind study, ten corn kernels showing bright greenish yellow fluorescence (BGYF) in the germ or endosperm and ten BGYF-negative kernels were correctly classified as infected or not infected by Fourier transform infrared photoacoustic spectroscopy. Earlier studies have shown that BGYF-positive kernels contain the bulk of the aflatoxin contaminating grain at harvest. Ten major spectral features, identified by visual inspection of the photoacoustic spectra of A. flavus mycelium grown in culture versus uninfected corn, were interpreted and assigned by theoretical comparisons of the relative chemical compositions of fungi and corn. The spectral features can be built into either empirical or knowledge-based computer models (expert systems) for automatic infrared detection and segregation of grains or kernels containing aflatoxin from the food and feed supply.

Separation of Atmospheric and Surface Spectral Features in Mars Global Surveyor Thermal Emission Spectrometer (TES) Spectra

NASA Technical Reports Server (NTRS)

Smith, Michael D.; Bandfield, Joshua L.; Christensen, Philip R.

2000-01-01

We present two algorithms for the separation of spectral features caused by atmospheric and surface components in Thermal Emission Spectrometer (TES) data. One algorithm uses radiative transfer and successive least squares fitting to find spectral shapes first for atmospheric dust, then for water-ice aerosols, and then, finally, for surface emissivity. A second independent algorithm uses a combination of factor analysis, target transformation, and deconvolution to simultaneously find dust, water ice, and surface emissivity spectral shapes. Both algorithms have been applied to TES spectra, and both find very similar atmospheric and surface spectral shapes. For TES spectra taken during aerobraking and science phasing periods in nadir-geometry these two algorithms give meaningful and usable surface emissivity spectra that can be used for mineralogical identification.

Single-Molecule Spectroscopy Unmasks the Lowest Exciton State of the B850 Assembly in LH2 from Rps. acidophila

PubMed Central

Kunz, Ralf; Timpmann, Kõu; Southall, June; Cogdell, Richard J.; Freiberg, Arvi; Köhler, Jürgen

2014-01-01

We have recorded fluorescence-excitation and emission spectra from single LH2 complexes from Rhodopseudomonas (Rps.) acidophila. Both types of spectra show strong temporal spectral fluctuations that can be visualized as spectral diffusion plots. Comparison of the excitation and emission spectra reveals that for most of the complexes the lowest exciton transition is not observable in the excitation spectra due to the cutoff of the detection filter characteristics. However, from the spectral diffusion plots we have the full spectral and temporal information at hand and can select those complexes for which the excitation spectra are complete. Correlating the red most spectral feature of the excitation spectrum with the blue most spectral feature of the emission spectrum allows an unambiguous assignment of the lowest exciton state. Hence, application of fluorescence-excitation and emission spectroscopy on the same individual LH2 complex allows us to decipher spectral subtleties that are usually hidden in traditional ensemble spectroscopy. PMID:24806933

Spectral reflectance properties (0.4-2.5 um) of secondary Fe-oxide, Fe-hydroxide, and Fe-sulfate-hydrate minerals associated with sulfide-bearing mine waste

USGS Publications Warehouse

Crowley, J.K.; Williams, D.E.; Hammarstrom1, J.M.; Piatak, N.; Mars, J.C.; Chou, I-Ming

2006-01-01

Fifteen Fe-oxide, Fe-hydroxide, and Fe-sulphate-hydrate mineral species commonly associated with sulphide bearing mine wastes were characterized by using X-ray powder diffraction and scanning electron microscope methods. Diffuse reflectance spectra of the samples show diagnostic absorption features related to electronic processes involving ferric and/or ferrous iron, and to vibrational processes involving water and hydroxyl ions. Such spectral features enable field and remote sensing based studies of the mineral distributions. Because secondary minerals are sensitive indicators of pH, Eh, relative humidity, and other environmental conditions, spectral mapping of these minerals promises to have important applications to mine waste remediation studies. This report releases digital (ascii) spectra (spectral_data_files.zip) of the fifteen mineral samples to facilitate usage of the data with spectral libraries and spectral analysis software. The spectral data are provided in a two-column format listing wavelength (in micrometers) and reflectance, respectively.

Multispectral processing without spectra.

PubMed

Drew, Mark S; Finlayson, Graham D

2003-07-01

It is often the case that multiplications of whole spectra, component by component, must be carried out,for example when light reflects from or is transmitted through materials. This leads to particularly taxing calculations, especially in spectrally based ray tracing or radiosity in graphics, making a full-spectrum method prohibitively expensive. Nevertheless, using full spectra is attractive because of the many important phenomena that can be modeled only by using all the physics at hand. We apply to the task of spectral multiplication a method previously used in modeling RGB-based light propagation. We show that we can often multiply spectra without carrying out spectral multiplication. In previous work [J. Opt. Soc. Am. A 11, 1553 (1994)] we developed a method called spectral sharpening, which took camera RGBs to a special sharp basis that was designed to render illuminant change simple to model. Specifically, in the new basis, one can effectively model illuminant change by using a diagonal matrix rather than the 3 x 3 linear transform that results from a three-component finite-dimensional model [G. Healey and D. Slater, J. Opt. Soc. Am. A 11, 3003 (1994)]. We apply this idea of sharpening to the set of principal components vectors derived from a representative set of spectra that might reasonably be encountered in a given application. With respect to the sharp spectral basis, we show that spectral multiplications can be modeled as the multiplication of the basis coefficients. These new product coefficients applied to the sharp basis serve to accurately reconstruct the spectral product. Although the method is quite general, we show how to use spectral modeling by taking advantage of metameric surfaces, ones that match under one light but not another, for tasks such as volume rendering. The use of metamers allows a user to pick out or merge different volume structures in real time simply by changing the lighting.

Multispectral processing without spectra

NASA Astrophysics Data System (ADS)

Drew, Mark S.; Finlayson, Graham D.

2003-07-01

It is often the case that multiplications of whole spectra, component by component, must be carried out, for example when light reflects from or is transmitted through materials. This leads to particularly taxing calculations, especially in spectrally based ray tracing or radiosity in graphics, making a full-spectrum method prohibitively expensive. Nevertheless, using full spectra is attractive because of the many important phenomena that can be modeled only by using all the physics at hand. We apply to the task of spectral multiplication a method previously used in modeling RGB-based light propagation. We show that we can often multiply spectra without carrying out spectral multiplication. In previous work J. Opt. Soc. Am. A 11 , 1553 (1994) we developed a method called spectral sharpening, which took camera RGBs to a special sharp basis that was designed to render illuminant change simple to model. Specifically, in the new basis, one can effectively model illuminant change by using a diagonal matrix rather than the 33 linear transform that results from a three-component finite-dimensional model G. Healey and D. Slater, J. Opt. Soc. Am. A 11 , 3003 (1994). We apply this idea of sharpening to the set of principal components vectors derived from a representative set of spectra that might reasonably be encountered in a given application. With respect to the sharp spectral basis, we show that spectral multiplications can be modeled as the multiplication of the basis coefficients. These new product coefficients applied to the sharp basis serve to accurately reconstruct the spectral product. Although the method is quite general, we show how to use spectral modeling by taking advantage of metameric surfaces, ones that match under one light but not another, for tasks such as volume rendering. The use of metamers allows a user to pick out or merge different volume structures in real time simply by changing the lighting. 2003 Optical Society of America

Study on Remote Sensing Image Characteristics of Ecological Land: Case Study of Original Ecological Land in the Yellow River Delta

NASA Astrophysics Data System (ADS)

An, G. Q.

2018-04-01

Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

[The changes in spectral features of the staple-food bamboos of giant panda after flowering].

PubMed

Liu, Xue-Hua; Wu, Yan

2012-12-01

Large-area flowering of the giant pandas' staple food is an important factor which can influence their survival. Therefore, it is necessary to predict the bamboo flowering. Foping Nature Reserve was taken as the study area. The research selected the giant pandas' staple-food bamboos Bashania fargesii, Fargesia qinlingensis and Fargesia dracocephala with different flowering situations (i. e., flowering, potential flowering, non-flowering with far distance) to measure the spectral reflectance of bamboo leaves. We studied the influence of bamboo flowering on the spectral features of three bamboo species through analyzing the original spectral reflectance and their red edge parameters. The results showed that (1) the flowering changed the spectra features of bamboo species. The spectral reflectance of B. fargesii shows a pattern: flowering bamboo < potential flowering bamboo < non-flowering bamboo with far distance, while F. qinlingensis and F. dracocephala show the different pattern: flowering bamboo > or = potential flowering bamboo > non-flowering bamboo with far distance. Among three bamboo species, F. dracocephala showed the greatest change, and then F. qinlingensis. (2) After bamboo flowering, the red edge of B. fargesii has no obvious shifting, while the other two bamboos have distinctive shifting towards the shorter waves. The study found that the original spectral feature and the red edge all changed under various flowering states, which can be used to provide the experimental basis and theoretic support for the future prediction of bamboo flowering through remote sensing.

Effects of band selection on endmember extraction for forestry applications

NASA Astrophysics Data System (ADS)

Karathanassi, Vassilia; Andreou, Charoula; Andronis, Vassilis; Kolokoussis, Polychronis

2014-10-01

In spectral unmixing theory, data reduction techniques play an important role as hyperspectral imagery contains an immense amount of data, posing many challenging problems such as data storage, computational efficiency, and the so called "curse of dimensionality". Feature extraction and feature selection are the two main approaches for dimensionality reduction. Feature extraction techniques are used for reducing the dimensionality of the hyperspectral data by applying transforms on hyperspectral data. Feature selection techniques retain the physical meaning of the data by selecting a set of bands from the input hyperspectral dataset, which mainly contain the information needed for spectral unmixing. Although feature selection techniques are well-known for their dimensionality reduction potentials they are rarely used in the unmixing process. The majority of the existing state-of-the-art dimensionality reduction methods set criteria to the spectral information, which is derived by the whole wavelength, in order to define the optimum spectral subspace. These criteria are not associated with any particular application but with the data statistics, such as correlation and entropy values. However, each application is associated with specific land c over materials, whose spectral characteristics present variations in specific wavelengths. In forestry for example, many applications focus on tree leaves, in which specific pigments such as chlorophyll, xanthophyll, etc. determine the wavelengths where tree species, diseases, etc., can be detected. For such applications, when the unmixing process is applied, the tree species, diseases, etc., are considered as the endmembers of interest. This paper focuses on investigating the effects of band selection on the endmember extraction by exploiting the information of the vegetation absorbance spectral zones. More precisely, it is explored whether endmember extraction can be optimized when specific sets of initial bands related to leaf spectral characteristics are selected. Experiments comprise application of well-known signal subspace estimation and endmember extraction methods on a hyperspectral imagery that presents a forest area. Evaluation of the extracted endmembers showed that more forest species can be extracted as endmembers using selected bands.

Constraining Cometary Crystal Shapes from IR Spectral Features

NASA Technical Reports Server (NTRS)

Wooden, Diane H.; Lindsay, Sean; Harker, David E.; Kelley, Michael S. P.; Woodward, Charles E.; Murphy, James Richard

2013-01-01

A major challenge in deriving the silicate mineralogy of comets is ascertaining how the anisotropic nature of forsterite crystals affects the spectral features' wavelength, relative intensity, and asymmetry. Forsterite features are identified in cometary comae near 10, 11.05-11.2, 16, 19, 23.5, 27.5 and 33 microns [1-10], so accurate models for forsterite's absorption efficiency (Qabs) are a primary requirement to compute IR spectral energy distributions (SEDs, lambdaF lambda vs. lambda) and constrain the silicate mineralogy of comets. Forsterite is an anisotropic crystal, with three crystallographic axes with distinct indices of refraction for the a-, b-, and c-axis. The shape of a forsterite crystal significantly affects its spectral features [13-16]. We need models that account for crystal shape. The IR absorption efficiencies of forsterite are computed using the discrete dipole approximation (DDA) code DDSCAT [11,12]. Starting from a fiducial crystal shape of a cube, we systematically elongate/reduce one of the crystallographic axes. Also, we elongate/reduce one axis while the lengths of the other two axes are slightly asymmetric (0.8:1.2). The most significant grain shape characteristic that affects the crystalline spectral features is the relative lengths of the crystallographic axes. The second significant grain shape characteristic is breaking the symmetry of all three axes [17]. Synthetic spectral energy distributions using seven crystal shape classes [17] are fit to the observed SED of comet C/1995 O1 (Hale-Bopp). The Hale-Bopp crystalline residual better matches equant, b-platelets, c-platelets, and b-columns spectral shape classes, while a-platelets, a-columns and c-columns worsen the spectral fits. Forsterite condensation and partial evaporation experiments demonstrate that environmental temperature and grain shape are connected [18-20]. Thus, grain shape is a potential probe for protoplanetary disk temperatures where the cometary crystalline forsterite formed. The forsterite crystal shapes (equant, b-platelets, c-platelets, b-columns - excluding a- and c-columns) derived from our modeling [17] of comet Hale- Bopp, compared to laboratory synthesis experiments [18], suggests that these crystals are high temperature condensates. By observing and modeling the crystalline features in comet ISON, we may constrain forsterite crystal shape(s) and link to their formation temperature(s) and environment(s).

On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements.

PubMed

Li, Zhan; Schaefer, Michael; Strahler, Alan; Schaaf, Crystal; Jupp, David

2018-04-06

The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales.

IAR signatures in the ionosphere: Modeling and observations at the Chibis-M microsatellite

NASA Astrophysics Data System (ADS)

Pilipenko, V.; Dudkin, D.; Fedorov, E.; Korepanov, V.; Klimov, S.

2017-02-01

A peculiar feature of geomagnetic variations at middle/low latitudes in the ULF band, just below the fundamental tone of the Schumann resonance, is the occurrence of a multi-band spectral resonant structure, observed by high-sensitivity induction magnetometers during nighttime. The occurrence of such spectral structure was commonly attributed to the Ionospheric Alfvén Resonator (IAR) in the upper ionosphere. Rather surprisingly, while ground observations of the IAR are ubiquitous, there are practically no reports on the IAR signatures from space missions. According to the new paradigm, the multi-band spectral structure excited by a lightning discharge is in fact produced by a regular sequence of an original pulse from a stroke and echo-pulses reflected from the IAR upper boundary. Upon the interaction of initial lightning-generated pulse with the anisotropic lower ionosphere, it partially penetrates into the ionosphere, travels up the ionosphere as an Alfvén pulse, and reflects back from the upper IAR boundary. The superposition of the initial pulse and echo-pulses produces spectra with multiple spectral peaks. Our modeling of Alfvénic pulse propagation in a system with the altitude profile of Alfven velocity modeling the realistic ionosphere has shown that IAR spectral signatures are to be evident only on the ground and above the IAR. Inside the IAR, the superposition of upward and downward propagating pulses produces a more complicated spectral pattern and the IAR spectral signatures deteriorate. We have used electric field data from the low-orbit Chibis-M microsatellite to search for IAR signatures in the ionosphere. We found evidence that the multi-band structure revealed by spectral analysis in the frequency range of interest is indeed the result of a sequence of lightning-produced pulses. According to the proposed conception it seems possible to comprehend why the IAR signatures are less evident in the ionosphere than on the ground.

Research on oral test modeling based on multi-feature fusion

NASA Astrophysics Data System (ADS)

Shi, Yuliang; Tao, Yiyue; Lei, Jun

2018-04-01

In this paper, the spectrum of speech signal is taken as an input of feature extraction. The advantage of PCNN in image segmentation and other processing is used to process the speech spectrum and extract features. And a new method combining speech signal processing and image processing is explored. At the same time of using the features of the speech map, adding the MFCC to establish the spectral features and integrating them with the features of the spectrogram to further improve the accuracy of the spoken language recognition. Considering that the input features are more complicated and distinguishable, we use Support Vector Machine (SVM) to construct the classifier, and then compare the extracted test voice features with the standard voice features to achieve the spoken standard detection. Experiments show that the method of extracting features from spectrograms using PCNN is feasible, and the fusion of image features and spectral features can improve the detection accuracy.

Contamination of the 5394 Å spectral region by telluric lines

NASA Astrophysics Data System (ADS)

Vince, I.; Vince, O.

2010-11-01

The spectral region in the vicinity of 5394 Å contains three prominent photospheric spectral lines, which can be used as a solar plasma diagnostic tool. The occurrence of telluric lines in this region is a potential source of systematic and random errors in these solar spectral lines. The goal of our investigation was to determine the telluric line contamination of this interesting spectral region. Several series of high-resolution solar spectra within an interval of about 4 Å around the 5394 Å wavelength were observed at different zenith distances of the Sun. Comparison of these spectra has permitted identification of telluric lines in this spectral interval. The observations were carried out with the horizontal solar spectrograph of the Heliophysical Observatory in Debrecen. Telluric feature blending was identified in the blue and red wings of the Fe I 5393.2 Å line, and in the local continuum of the Mn I 5394.7 Å line. The blue wing of the Fe I 5395.2 Å line is contaminated by a weak telluric feature too. The red continuum of this line has a more prominent telluric contamination. A dozen of water vapor telluric lines that determined the observed telluric features were identified in this spectral interval. The profiles of three telluric lines that have a significant influence on both the profiles of solar spectral lines and the level of local continuum were derived, and the variation of their parameters (equivalent width and central depth) with air mass were analyzed.

An oil film information retrieval method overcoming the influence of sun glitter, based on AISA+ airborne hyper-spectral image

NASA Astrophysics Data System (ADS)

Zhan, Yuanzeng; Mao, Tianming; Gong, Fang; Wang, Difeng; Chen, Jianyu

2010-10-01

As an effective survey tool for oil spill detection, the airborne hyper-spectral sensor affords the potentiality for retrieving the quantitative information of oil slick which is useful for the cleanup of spilled oil. But many airborne hyper-spectral images are affected by sun glitter which distorts radiance values and spectral ratios used for oil slick detection. In 2005, there's an oil spill event leaking at oil drilling platform in The South China Sea, and an AISA+ airborne hyper-spectral image recorded this event will be selected for studying in this paper, which is affected by sun glitter terribly. Through a spectrum analysis of the oil and water samples, two features -- "spectral rotation" and "a pair of fixed points" can be found in spectral curves between crude oil film and water. Base on these features, an oil film information retrieval method which can overcome the influence of sun glitter is presented. Firstly, the radiance of the image is converted to normal apparent reflectance (NormAR). Then, based on the features of "spectral rotation" (used for distinguishing oil film and water) and "a pair of fixed points" (used for overcoming the effect of sun glitter), NormAR894/NormAR516 is selected as an indicator of oil film. Finally, by using a threshold combined with the technologies of image filter and mathematic morphology, the distribution and relative thickness of oil film are retrieved.

Characterization of protein and carbohydrate mid-IR spectral features in crop residues

NASA Astrophysics Data System (ADS)

Xin, Hangshu; Zhang, Yonggen; Wang, Mingjun; Li, Zhongyu; Wang, Zhibo; Yu, Peiqiang

2014-08-01

To the best of our knowledge, a few studies have been conducted on inherent structure spectral traits related to biopolymers of crop residues. The objective of this study was to characterize protein and carbohydrate structure spectral features of three field crop residues (rice straw, wheat straw and millet straw) in comparison with two crop vines (peanut vine and pea vine) by using Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR). Also, multivariate analyses were performed on spectral data sets within the regions mainly related to protein and carbohydrate in this study. The results showed that spectral differences existed in mid-IR peak intensities that are mainly related to protein and carbohydrate among these crop residue samples. With regard to protein spectral profile, peanut vine showed the greatest mid-IR band intensities that are related to protein amide and protein secondary structures, followed by pea vine and the rest three field crop straws. The crop vines had 48-134% higher spectral band intensity than the grain straws in spectral features associated with protein. Similar trends were also found in the bands that are mainly related to structural carbohydrates (such as cellulosic compounds). However, the field crop residues had higher peak intensity in total carbohydrates region than the crop vines. Furthermore, spectral ratios varied among the residue samples, indicating that these five crop residues had different internal structural conformation. However, multivariate spectral analyses showed that structural similarities still exhibited among crop residues in the regions associated with protein biopolymers and carbohydrate. Further study is needed to find out whether there is any relationship between spectroscopic information and nutrition supply in various kinds of crop residue when fed to animals.

Characterization of protein and carbohydrate mid-IR spectral features in crop residues.

PubMed

Xin, Hangshu; Zhang, Yonggen; Wang, Mingjun; Li, Zhongyu; Wang, Zhibo; Yu, Peiqiang

2014-08-14

To the best of our knowledge, a few studies have been conducted on inherent structure spectral traits related to biopolymers of crop residues. The objective of this study was to characterize protein and carbohydrate structure spectral features of three field crop residues (rice straw, wheat straw and millet straw) in comparison with two crop vines (peanut vine and pea vine) by using Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR). Also, multivariate analyses were performed on spectral data sets within the regions mainly related to protein and carbohydrate in this study. The results showed that spectral differences existed in mid-IR peak intensities that are mainly related to protein and carbohydrate among these crop residue samples. With regard to protein spectral profile, peanut vine showed the greatest mid-IR band intensities that are related to protein amide and protein secondary structures, followed by pea vine and the rest three field crop straws. The crop vines had 48-134% higher spectral band intensity than the grain straws in spectral features associated with protein. Similar trends were also found in the bands that are mainly related to structural carbohydrates (such as cellulosic compounds). However, the field crop residues had higher peak intensity in total carbohydrates region than the crop vines. Furthermore, spectral ratios varied among the residue samples, indicating that these five crop residues had different internal structural conformation. However, multivariate spectral analyses showed that structural similarities still exhibited among crop residues in the regions associated with protein biopolymers and carbohydrate. Further study is needed to find out whether there is any relationship between spectroscopic information and nutrition supply in various kinds of crop residue when fed to animals. Copyright © 2014 Elsevier B.V. All rights reserved.

How Does the Shape of the Stellar Spectrum Affect the Raman Scattering Features in the Albedo of Exoplanets?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oklopčić, Antonija; Hirata, Christopher M.; Heng, Kevin, E-mail: oklopcic@astro.caltech.edu

The diagnostic potential of the spectral signatures of Raman scattering, imprinted in planetary albedo spectra at short optical wavelengths, has been demonstrated in research on planets in the solar system, and has recently been proposed as a probe of exoplanet atmospheres, complementary to albedo studies at longer wavelengths. Spectral features caused by Raman scattering offer insight into the properties of planetary atmospheres, such as the atmospheric depth, composition, and temperature, as well as the possibility of detecting and spectroscopically identifying spectrally inactive species, such as H{sub 2} and N{sub 2}, in the visible wavelength range. Raman albedo features, however, dependmore » on both the properties of the atmosphere and the shape of the incident stellar spectrum. Identical planetary atmospheres can produce very different albedo spectra depending on the spectral properties of the host star. Here we present a set of geometric albedo spectra calculated for atmospheres with H{sub 2}/He, N{sub 2}, and CO{sub 2} composition, irradiated by different stellar types ranging from late A to late K stars. Prominent albedo features caused by Raman scattering appear at different wavelengths for different types of host stars. We investigate how absorption due to the alkali elements sodium and potassium may affect the intensity of Raman features, and we discuss the preferred strategies for detecting Raman features in future observations.« less

A spectral reflectance estimation technique using multispectral data from the Viking lander camera

NASA Technical Reports Server (NTRS)

Park, S. K.; Huck, F. O.

1976-01-01

A technique is formulated for constructing spectral reflectance curve estimates from multispectral data obtained with the Viking lander camera. The multispectral data are limited to six spectral channels in the wavelength range from 0.4 to 1.1 micrometers and most of these channels exhibit appreciable out-of-band response. The output of each channel is expressed as a linear (integral) function of the (known) solar irradiance, atmospheric transmittance, and camera spectral responsivity and the (unknown) spectral responsivity and the (unknown) spectral reflectance. This produces six equations which are used to determine the coefficients in a representation of the spectral reflectance as a linear combination of known basis functions. Natural cubic spline reflectance estimates are produced for a variety of materials that can be reasonably expected to occur on Mars. In each case the dominant reflectance features are accurately reproduced, but small period features are lost due to the limited number of channels. This technique may be a valuable aid in selecting the number of spectral channels and their responsivity shapes when designing a multispectral imaging system.

Classifying Human Voices by Using Hybrid SFX Time-Series Preprocessing and Ensemble Feature Selection

PubMed Central

Wong, Raymond

2013-01-01

Voice biometrics is one kind of physiological characteristics whose voice is different for each individual person. Due to this uniqueness, voice classification has found useful applications in classifying speakers' gender, mother tongue or ethnicity (accent), emotion states, identity verification, verbal command control, and so forth. In this paper, we adopt a new preprocessing method named Statistical Feature Extraction (SFX) for extracting important features in training a classification model, based on piecewise transformation treating an audio waveform as a time-series. Using SFX we can faithfully remodel statistical characteristics of the time-series; together with spectral analysis, a substantial amount of features are extracted in combination. An ensemble is utilized in selecting only the influential features to be used in classification model induction. We focus on the comparison of effects of various popular data mining algorithms on multiple datasets. Our experiment consists of classification tests over four typical categories of human voice data, namely, Female and Male, Emotional Speech, Speaker Identification, and Language Recognition. The experiments yield encouraging results supporting the fact that heuristically choosing significant features from both time and frequency domains indeed produces better performance in voice classification than traditional signal processing techniques alone, like wavelets and LPC-to-CC. PMID:24288684

USGS Digital Spectral Library splib06a

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Wise, Richard A.; Livo, K. Eric; Hoefen, Todd M.; Kokaly, Raymond F.; Sutley, Stephen J.

2007-01-01

Introduction We have assembled a digital reflectance spectral library that covers the wavelength range from the ultraviolet to far infrared along with sample documentation. The library includes samples of minerals, rocks, soils, physically constructed as well as mathematically computed mixtures, plants, vegetation communities, microorganisms, and man-made materials. The samples and spectra collected were assembled for the purpose of using spectral features for the remote detection of these and similar materials. Analysis of spectroscopic data from laboratory, aircraft, and spacecraft instrumentation requires a knowledge base. The spectral library discussed here forms a knowledge base for the spectroscopy of minerals and related materials of importance to a variety of research programs being conducted at the U.S. Geological Survey. Much of this library grew out of the need for spectra to support imaging spectroscopy studies of the Earth and planets. Imaging spectrometers, such as the National Aeronautics and Space Administration (NASA) Airborne Visible/Infra Red Imaging Spectrometer (AVIRIS) or the NASA Cassini Visual and Infrared Mapping Spectrometer (VIMS) which is currently orbiting Saturn, have narrow bandwidths in many contiguous spectral channels that permit accurate definition of absorption features in spectra from a variety of materials. Identification of materials from such data requires a comprehensive spectral library of minerals, vegetation, man-made materials, and other subjects in the scene. Our research involves the use of the spectral library to identify the components in a spectrum of an unknown. Therefore, the quality of the library must be very good. However, the quality required in a spectral library to successfully perform an investigation depends on the scientific questions to be answered and the type of algorithms to be used. For example, to map a mineral using imaging spectroscopy and the mapping algorithm of Clark and others (1990a, 2003b), one simply needs a diagnostic absorption band. The mapping system uses continuum-removed reference spectral features fitted to features in observed spectra. Spectral features for such algorithms can be obtained from a spectrum of a sample containing large amounts of contaminants, including those that add other spectral features, as long as the shape of the diagnostic feature of interest is not modified. If, however, the data are needed for radiative transfer models to derive mineral abundances from reflectance spectra, then completely uncontaminated spectra are required. This library contains spectra that span a range of quality, with purity indicators to flag spectra for (or against) particular uses. Acquiring spectral measurements and performing sample characterizations for this library has taken about 15 person-years of effort. Software to manage the library and provide scientific analysis capability is provided (Clark, 1980, 1993). A personal computer (PC) reader for the library is also available (Livo and others, 1993). The program reads specpr binary files (Clark, 1980, 1993) and plots spectra. Another program that reads the specpr format is written in IDL (Kokaly, 2005). In our view, an ideal spectral library consists of samples covering a very wide range of materials, has large wavelength range with very high precision, and has enough sample analyses and documentation to establish the quality of the spectra. Time and available resources limit what can be achieved. Ideally, for each mineral, the sample analysis would include X-ray diffraction (XRD), electron microprobe (EM) or X-ray fluorescence (XRF), and petrographic microscopic analyses. For some minerals, such as iron oxides, additional analyses such as Mossbauer would be helpful. We have found that to make the basic spectral measurements, provide XRD, EM or XRF analyses, and microscopic analyses, document the results, and complete an entry of one spectral library sample, all takes about

Device, Algorithm and Integrated Modeling Research for Performance-Drive Multi-Modal Optical Sensors

DTIC Science & Technology

2012-12-17

to!feature!aided!tracking! using !spectral! information .! ! !iii! •! A!novel!technique!for!spectral!waveband!selection!was!developed!and! used !as! part! of ... of !spectral! information ! using !the!tunable!single;pixel!spectrometer!concept.! •! A! database! was! developed! of ! spectral! reflectance! measurements...exploring! the! utility! of ! spectral! and! polarimetric! information !to!help!with!the!vehicle!tracking!application.!Through!the! use ! of ! both

Coupled atmosphere/canopy model for remote sensing of plant reflectance features

NASA Technical Reports Server (NTRS)

Gerstl, S. A.; Zardecki, A.

1985-01-01

Solar radiative transfer through a coupled system of atmosphere and plant canopy is modeled as a multiple-scattering problem through a layered medium of random scatterers. The radiative transfer equation is solved by the discrete-ordinates finite-element method. Analytic expressions are derived that allow the calculation of scattering and absorption cross sections for any plant canopy layer form measurable biophysical parameters such as the leaf area index, leaf angle distribution, and individual leaf reflectance and transmittance data. An expression for a canopy scattering phase function is also given. Computational results are in good agreement with spectral reflectance measurements directly above a soybean canopy, and the concept of greenness- and brightness-transforms of Landsat MSS data is reconfirmed with the computed results. A sensitivity analysis with the coupled atmosphere/canopy model quantifies how satellite-sensed spectral radiances are affected by increased atmospheric aerosols, by varying leaf area index, by anisotropic leaf scattering, and by non-Lambertian soil boundary conditions. Possible extensions to a 2-D model are also discussed.

Time-Resolved Investigations of Heterobimetallic Cofactor Assembly in R2lox Reveal Distinct Mn/Fe Intermediates.

PubMed

Miller, Effie K; Trivelas, Nicholas E; Maugeri, Pearson T; Blaesi, Elizabeth J; Shafaat, Hannah S

2017-07-05

The assembly mechanism of the Mn/Fe ligand-binding oxidases (R2lox), a family of proteins that are homologous to the nonheme diiron carboxylate enzymes, has been investigated using time-resolved techniques. Multiple heterobimetallic intermediates that exhibit unique spectral features, including visible absorption bands and exceptionally broad electron paramagnetic resonance signatures, are observed through optical and magnetic resonance spectroscopies. On the basis of comparison to known diiron species and model compounds, the spectra have been attributed to (μ-peroxo)-Mn III /Fe III and high-valent Mn/Fe species. Global spectral analysis coupled with isotopic substitution and kinetic modeling reveals elementary rate constants for the assembly of Mn/Fe R2lox under aerobic conditions. A complete reaction mechanism for cofactor maturation that is consistent with experimental data has been developed. These results suggest that the Mn/Fe cofactor can perform direct C-H bond abstraction, demonstrating the potential for potent chemical reactivity that remains unexplored.

A Study on Spectral Signature Analysis of Wetland Vegetation Based on Ground Imaging Spectrum Data

NASA Astrophysics Data System (ADS)

Ling, Chengxing; Liu, Hua; Ju, Hongbo; Zhang, Huaiqing; You, Jia; Li, Weina

2017-10-01

The objective of this study was to verify the application of imaging spectrometer in wetland vegetation remote sensing monitoring, based on analysis of wetland vegetation spectral features. Spectral information of Carex vegetation spectral data under different water environment was collected bySOC710VP and ASD FieldSpec 3; Meanwhile, the chlorophyll contents of wheat leaves were tested in the lab. A total 9 typical vegetation indices were calculated by using two instruments’ data which were spectral values from 400nm to 1000 nm. Then features between the same vegetation indices and soil water contents for two applications were analyzed and compared. The results showed that there were same spectrum curve trends of Carex vegetation (soil moisture content of 51%, 32%, 14% and three regional comparative analysis)reflectance between SOC710VP and ASD FieldSpec 3, including the two reflectance peak of 550nm and 730 nm, two reflectance valley of 690 nm and 970nm, and continuous near infrared reflectance platform. However, The two also have a very clear distinction: (1) The reflection spectra of SOC710VP leaves of Carex Carex leaf spectra in the three soil moisture environment values are greater than ASD FieldSpec 3 collected value; (2) The SOC710VP reflectivity curve does not have the smooth curve of the original spectrum measured by the ASD FieldSpec 3, the amplitude of fluctuation is bigger, and it is more obvious in the near infrared band. It is concluded that SOC710VP spectral data are reliable, with the image features, spectral curve features reliable. It has great potential in the research of hyperspectral remote sensing technology in the development of wetland near earth, remote sensing monitoring of wetland resources.

The effect of time-variant acoustical properties on orchestral instrument timbres

NASA Astrophysics Data System (ADS)

Hajda, John Michael

1999-06-01

The goal of this study was to investigate the timbre of orchestral instrument tones. Kendall (1986) showed that time-variant features are important to instrument categorization. But the relative salience of specific time-variant features to each other and to other acoustical parameters is not known. As part of a convergence strategy, a battery of experiments was conducted to assess the importance of global amplitude envelope, spectral frequencies, and spectral amplitudes. An omnibus identification experiment investigated the salience of global envelope partitions (attack, steady state, and decay). Valid partitioning models should identify important boundary conditions in the evolution of a signal; therefore, these models should be based on signal characteristics. With the use of such a model for sustained continuant tones, the steady-state segment was more salient than the attack. These findings contradicted previous research, which used questionable operational definitions for signal partitioning. For the next set of experiments, instrument tones were analyzed by phase vocoder, and stimuli were created by additive synthesis. Edits and combinations of edits controlled global amplitude envelope, spectral frequencies, and relative spectral amplitudes. Perceptual measurements were made with distance estimation, Verbal Attribute Magnitude Estimation, and similarity scaling. Results indicated that the primary acoustical attribute was the long-time-average spectral centroid. Spectral centroid is a measure of the center of energy distribution for spectral frequency components. Instruments with high values of spectral centroid (bowed strings) sound nasal while instruments with low spectral centroid (flute, clarinet) sound not nasal. The secondary acoustical attribute was spectral amplitude time variance. Predictably, time variance correlated highly with subject ratings of vibrato. The control of relative spectral amplitudes was more salient than the control of global envelope and spectral frequencies. Both amplitude phase relationships and time- variant spectral centroid were affected by the control of relative spectral amplitudes. Further experimentation is required to determine the salience of these features. The finding that instrumental vibrato is a manifestation of spectral amplitude time variance contradicts the common belief that vibrato is due to frequency (pitch) and intensity (loudness) modulation. This study suggests that vibrato is due to a periodic modulation in timbre. Future research should employ musical contexts.

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues. PMID:22403724

Composition and structure of fresh ammonia clouds on Jupiter based on quantitative analysis of Galileo/NIMS and New Horizons/LEISA spectra

NASA Astrophysics Data System (ADS)

Sromovsky, L. A.; Fry, P. M.

2018-06-01

Ammonia gas has long been assumed to be the main source of condensables for the upper cloud layer on Jupiter, but distinctive spectral features associated with ammonia have been seen only rarely. Since both ammonia and NH4SH absorb in the 3 μm region, and widespread absorption in the 3 μm region was present (Sromovsky and Fry, 2010), identification of the 2 μm absorption feature of NH3 provided an opportunity to clearly establish its presence in Jovian clouds. Baines et al. (2002) succeeded in finding in Near Infrared Mapping Spectrometer (NIMS) observations one feature that had both 2 μm and 3 μm absorption, and many which were known to have absorption at 2.73 μm. They named these Spectrally Identifiable Ammonia Clouds (SIACs). They also argued that these were fresh ammonia clouds that would eventually succumb to some process that would obscure their absorption features. Detection of many more of the 2 μm features was later achieved by New Horizon's Linear Etalon Imaging Spectral Array (LEISA) instrument, which provided both the spatial and spectral resolution needed to identify these features. Here we report on the first quantitative modeling that uses NIMS spectra over a broad (1-5.2 μm) spectral range and LEISA spectra over a much narrower (1.25-2.5 μm) spectral range to constrain the cloud structure and composition of these rare cloud features and compare them to background clouds. We find that the absorption signature at 2 μm, which is well characterized in LEISA spectra, is relatively subtle and easily matched by model clouds containing spherical particles of ammonia ice with radii of 2-4 μm. The NIMS spectra, which cover both reflected sunlight as well as thermal emission regions are more difficult to model with cloud materials plausibly present in Jupiter's atmosphere. The best signal/noise spectra obtained from NIMS provide a relatively sparse sampling of the spectrum, which does not establish the detailed shape of the 3 μm absorption region. NIMS SIAC spectra with much denser spectral sampling are limited by much higher noise levels that degrade the features that are key to identifying cloud composition. The structure which best matches the wide range NIMS SIAC spectra contains two overlapping NH3 clouds with a bi-modal size distribution over an optically thick NH4SH cloud. The bi-modal distribution may be a result of modeling non-spherical, possibly fractal aggregate, particles with spheres.

Distinctive Features of NREM Parasomnia Behaviors in Parkinson’s Disease and Multiple System Atrophy

PubMed Central

Ratti, Pietro-Luca; Sierra-Peña, Maria; Manni, Raffaele; Simonetta-Moreau, Marion; Bastin, Julien; Mace, Harrison; Rascol, Olivier; David, Olivier

2015-01-01

Objective To characterize parasomnia behaviors on arousal from NREM sleep in Parkinson’s Disease (PD) and Multiple System Atrophy (MSA). Methods From 30 patients with PD, Dementia with Lewy Bodies/Dementia associated with PD, or MSA undergoing nocturnal video-polysomnography for presumed dream enactment behavior, we were able to select 2 PD and 2 MSA patients featuring NREM Parasomnia Behviors (NPBs). We identified episodes during which the subjects seemed to enact dreams or presumed dream-like mentation (NPB arousals) versus episodes with physiological movements (no-NPB arousals). A time-frequency analysis (Morlet Wavelet Transform) of the scalp EEG signals around each NPB and no- NPB arousal onset was performed, and the amplitudes of the spectral frequencies were compared between NPB and no-NPB arousals. Results 19 NPBs were identified, 12 of which consisting of ‘elementary’ NPBs while 7 resembling confusional arousals. With quantitative EEG analysis, we found an amplitude reduction in the 5-6 Hz band 40 seconds before NPBs arousal as compared to no-NPB arousals at F4 and C4 derivations (p<0.01). Conclusions Many PD and MSA patients feature various NREM sleep-related behaviors, with clinical and electrophysiological differences and similarities with arousal parasomnias in the general population. Significance This study help bring to attention an overlooked phenomenon in neurodegenerative diseases. PMID:25756280

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Yiying, E-mail: yiyingyan@sjtu.edu.cn; Lü, Zhiguo, E-mail: zglv@sjtu.edu.cn; Zheng, Hang, E-mail: hzheng@sjtu.edu.cn

We present a theoretical formalism for resonance fluorescence radiating from a two-level system (TLS) driven by any periodic driving and coupled to multiple reservoirs. The formalism is derived analytically based on the combination of Floquet theory and Born–Markov master equation. The formalism allows us to calculate the spectrum when the Floquet states and quasienergies are analytically or numerically solved for simple or complicated driving fields. We can systematically explore the spectral features by implementing the present formalism. To exemplify this theory, we apply the unified formalism to comprehensively study a generic model that a harmonically driven TLS is simultaneously coupledmore » to a radiative reservoir and a dephasing reservoir. We demonstrate that the significant features of the fluorescence spectra, the driving-induced asymmetry and the dephasing-induced asymmetry, can be attributed to the violation of detailed balance condition, and explained in terms of the driving-related transition quantities between Floquet-states and their steady populations. In addition, we find the distinguished features of the fluorescence spectra under the biharmonic and multiharmonic driving fields in contrast with that of the harmonic driving case. In the case of the biharmonic driving, we find that the spectra are significantly different from the result of the RWA under the multiple resonance conditions. By the three concrete applications, we illustrate that the present formalism provides a routine tool for comprehensively exploring the fluorescence spectrum of periodically strongly driven TLSs.« less

The very high rotators in the late-B and early-A stars: Shell stars with Si IV and C IV features the case of HD 119921

NASA Technical Reports Server (NTRS)

Freireferrero, R.; Bruhweiler, Frederick C.; Grady, C. A.

1990-01-01

Study of several stars in the late B and early A spectral types shows that very high rotators are associated with shell characteristics (sometimes not detected at all in the visible spectra) and also with C IV and some Si IV spectral absorption features which can be explained by circumstellar phenomena superimposed over stellar metallic blends. These particularities are evidenced by comparison with other spectra of low and high rotators in the same spectral range. HD 119921, a star with similar characteristics to the other ones of the sample, is given special attention. A possible scenario is suggested to explain the observed superionization features.

Progressively expanded neural network for automatic material identification in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Paheding, Sidike

The science of hyperspectral remote sensing focuses on the exploitation of the spectral signatures of various materials to enhance capabilities including object detection, recognition, and material characterization. Hyperspectral imagery (HSI) has been extensively used for object detection and identification applications since it provides plenty of spectral information to uniquely identify materials by their reflectance spectra. HSI-based object detection algorithms can be generally classified into stochastic and deterministic approaches. Deterministic approaches are comparatively simple to apply since it is usually based on direct spectral similarity such as spectral angles or spectral correlation. In contrast, stochastic algorithms require statistical modeling and estimation for target class and non-target class. Over the decades, many single class object detection methods have been proposed in the literature, however, deterministic multiclass object detection in HSI has not been explored. In this work, we propose a deterministic multiclass object detection scheme, named class-associative spectral fringe-adjusted joint transform correlation. Human brain is capable of simultaneously processing high volumes of multi-modal data received every second of the day. In contrast, a machine sees input data simply as random binary numbers. Although machines are computationally efficient, they are inferior when comes to data abstraction and interpretation. Thus, mimicking the learning strength of human brain has been current trend in artificial intelligence. In this work, we present a biological inspired neural network, named progressively expanded neural network (PEN Net), based on nonlinear transformation of input neurons to a feature space for better pattern differentiation. In PEN Net, discrete fixed excitations are disassembled and scattered in the feature space as a nonlinear line. Each disassembled element on the line corresponds to a pattern with similar features. Unlike the conventional neural network where hidden neurons need to be iteratively adjusted to achieve better accuracy, our proposed PEN Net does not require hidden neurons tuning which achieves better computational efficiency, and it has also shown superior performance in HSI classification tasks compared to the state-of-the-arts. Spectral-spatial features based HSI classification framework has shown stronger strength compared to spectral-only based methods. In our lastly proposed technique, PEN Net is incorporated with multiscale spatial features (i.e., multiscale complete local binary pattern) to perform a spectral-spatial classification of HSI. Several experiments demonstrate excellent performance of our proposed technique compared to the more recent developed approaches.

ON THE LATE-TIME SPECTRAL SOFTENING FOUND IN X-RAY AFTERGLOWS OF GAMMA-RAY BURSTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Yuan-Zhu; Liang, En-Wei; Lu, Zu-Jia

2016-02-20

Strong spectral softening has been revealed in the late X-ray afterglows of some gamma-ray bursts (GRBs). The scenario of X-ray scattering around the circumburst dusty medium has been supported by previous works due to its overall successful prediction of both the temporal and spectral evolution of some X-ray afterglows. To further investigate the observed feature of spectral softening we now systematically search the X-ray afterglows detected by the X-ray telescope aboard Swift and collect 12 GRBs with significant late-time spectral softening. We find that dust scattering could be the dominant radiative mechanism for these X-ray afterglows regarding their temporal andmore » spectral features. For some well-observed bursts with high-quality data, the time-resolved spectra could be well-produced within the scattering scenario by taking into account the X-ray absorption from the circumburst medium. We also find that during spectral softening the power-law index in the high-energy end of the spectra does not vary much. The spectral softening is mainly manifested by the spectral peak energy continually moving to the soft end.« less

Probing collective oscillation of d -orbital electrons at the nanoscale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dhall, Rohan; Vigil-Fowler, Derek; Houston Dycus, J.

Here, we demonstrate that high energy electrons can be used to explore the collective oscillation of s, p, and d orbital electrons at the nanometer length scale. Using epitaxial AlGaN/AlN quantum wells as a test system, we observe the emergence of additional features in the loss spectrum with the increasing Ga content. A comparison of the observed spectra with ab-initio theory reveals that the origin of these spectral features lies in excitations of 3d-electrons contributed by Ga. We find that these modes differ in energy from the valence electron plasmons in Al1-xGaxN due to the different polarizabilities of the dmore » electrons. Finally, we study the dependence of observed spectral features on the Ga content, lending insights into the origin of these spectral features, and their coupling with electron-hole excitations.« less

Globally scalable generation of high-resolution land cover from multispectral imagery

NASA Astrophysics Data System (ADS)

Stutts, S. Craig; Raskob, Benjamin L.; Wenger, Eric J.

2017-05-01

We present an automated method of generating high resolution ( 2 meter) land cover using a pattern recognition neural network trained on spatial and spectral features obtained from over 9000 WorldView multispectral images (MSI) in six distinct world regions. At this resolution, the network can classify small-scale objects such as individual buildings, roads, and irrigation ponds. This paper focuses on three key areas. First, we describe our land cover generation process, which involves the co-registration and aggregation of multiple spatially overlapping MSI, post-aggregation processing, and the registration of land cover to OpenStreetMap (OSM) road vectors using feature correspondence. Second, we discuss the generation of land cover derivative products and their impact in the areas of region reduction and object detection. Finally, we discuss the process of globally scaling land cover generation using cloud computing via Amazon Web Services (AWS).

Utilization of satellite data for inventorying prairie ponds and lakes

USGS Publications Warehouse

Work, E.A.; Gilmer, D.S.

1976-01-01

By using data acquired by LANDSAT-1 (formerly ERTS- 1), studies were conducted in extracting information necessary for formulating management decisions relating to migratory waterfowl. Management decisions are based in part on an assessment ofhabitat characteristics, specifically numbers, distribution, and quality of ponds and lakes in the prime breeding range. This paper reports on a study concerned with mapping open surface water features in the glaciated prairies. Emphasis was placed on the recognition of these features based upon water's uniquely low radiance in a single nearinfrared waveband. The results of this recognition were thematic maps and statistics relating to open surface water. In a related effort, the added information content of multiple spectral wavebands was used for discriminating surface water at a level of detail finer than the virtual resolution of the data. The basic theory of this technique and some preliminary results are described.

Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing

NASA Astrophysics Data System (ADS)

Fan, Lei

Hyperspectral imaging provides the capability of increased sensitivity and discrimination over traditional imaging methods by combining standard digital imaging with spectroscopic methods. For each individual pixel in a hyperspectral image (HSI), a continuous spectrum is sampled as the spectral reflectance/radiance signature to facilitate identification of ground cover and surface material. The abundant spectrum knowledge allows all available information from the data to be mined. The superior qualities within hyperspectral imaging allow wide applications such as mineral exploration, agriculture monitoring, and ecological surveillance, etc. The processing of massive high-dimensional HSI datasets is a challenge since many data processing techniques have a computational complexity that grows exponentially with the dimension. Besides, a HSI dataset may contain a limited number of degrees of freedom due to the high correlations between data points and among the spectra. On the other hand, merely taking advantage of the sampled spectrum of individual HSI data point may produce inaccurate results due to the mixed nature of raw HSI data, such as mixed pixels, optical interferences and etc. Fusion strategies are widely adopted in data processing to achieve better performance, especially in the field of classification and clustering. There are mainly three types of fusion strategies, namely low-level data fusion, intermediate-level feature fusion, and high-level decision fusion. Low-level data fusion combines multi-source data that is expected to be complementary or cooperative. Intermediate-level feature fusion aims at selection and combination of features to remove redundant information. Decision level fusion exploits a set of classifiers to provide more accurate results. The fusion strategies have wide applications including HSI data processing. With the fast development of multiple remote sensing modalities, e.g. Very High Resolution (VHR) optical sensors, LiDAR, etc., fusion of multi-source data can in principal produce more detailed information than each single source. On the other hand, besides the abundant spectral information contained in HSI data, features such as texture and shape may be employed to represent data points from a spatial perspective. Furthermore, feature fusion also includes the strategy of removing redundant and noisy features in the dataset. One of the major problems in machine learning and pattern recognition is to develop appropriate representations for complex nonlinear data. In HSI processing, a particular data point is usually described as a vector with coordinates corresponding to the intensities measured in the spectral bands. This vector representation permits the application of linear and nonlinear transformations with linear algebra to find an alternative representation of the data. More generally, HSI is multi-dimensional in nature and the vector representation may lose the contextual correlations. Tensor representation provides a more sophisticated modeling technique and a higher-order generalization to linear subspace analysis. In graph theory, data points can be generalized as nodes with connectivities measured from the proximity of a local neighborhood. The graph-based framework efficiently characterizes the relationships among the data and allows for convenient mathematical manipulation in many applications, such as data clustering, feature extraction, feature selection and data alignment. In this thesis, graph-based approaches applied in the field of multi-source feature and data fusion in remote sensing area are explored. We will mainly investigate the fusion of spatial, spectral and LiDAR information with linear and multilinear algebra under graph-based framework for data clustering and classification problems.

Surface Composition of Trojan Asteroids from Thermal-Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

Martin, A.; Emery, J. P.; Lindsay, S. S.

2017-12-01

Asteroid origins provide an effective means of constraining the events that dynamically shaped the solar system. Jupiter Trojan asteroids (hereafter Trojans) may help in determining the extent of radial mixing that occurred during giant planet migration. Previous studies aimed at characterizing surface composition show that Trojans have low albedo surfaces and fall into two distinct spectral groups the near infrared (NIR). Though, featureless in this spectral region, NIR spectra of Trojans either exhibit a red or less-red slope. Typically, red-sloped spectra are associated with organics, but it has been shown that Trojans are not host to much, if any, organic material. Instead, the red slope is likely due to anhydrous silicates. The thermal infrared (TIR) wavelength range has advantages for detecting silicates on low albedo asteroids such as Trojans. The 10 µm region exhibits strong features due to the Si-O fundamental molecular vibrations. We hypothesize that the two Trojan spectral groups have different compositions (silicate mineralogy). With TIR spectra from the Spitzer Space Telescope, we identify mineralogical features from the surface of 11 Trojan asteroids, five red and six less-red. Preliminary results from analysis of the 10 µm region indicate red-sloped Trojans have a higher spectral contrast compared to less-red-sloped Trojans. Fine-grain mixtures of crystalline pyroxene and olivine exhibit a 10 µm feature with sharp cutoffs between about 9 µm and 12 µm, which create a broad flat plateau. Amorphous phases, when present, smooth the sharp emission features, resulting in a dome-like shape. Further spectral analysis in the 10 µm, 18 µm, and 30 µm band region will be performed for a more robust analysis. If all Trojans come from the same region, it is expected that they share spectral and compositional characteristics. Therefore, if spectral analysis in the TIR reinforce the NIR spectral slope dichotomy, it is likely that Trojans were sourced from two different regions of the solar system. This result would provide new constraints for dynamical models that explain giant planet migration.

Opportunities and challenges in industrial plantation mapping in big data era

NASA Astrophysics Data System (ADS)

Dong, J.; Xiao, X.; Qin, Y.; Chen, B.; Wang, J.; Kou, W.; Zhai, D.

2017-12-01

With the increasing demand in timer, rubber, palm oil in the world market, industrial plantations have dramatically expanded, especially in Southeast Asia; which have been affecting ecosystem services and human wellbeing. However, existing efforts on plantation mapping are still limited and blocked our understanding about the magnitude of plantation expansion and their potential environmental effects. Here we would present a literature review about the existing efforts on plantation mapping based on one or multiple remote sensing sources, including rubber, oil palm, and eucalyptus plantations. The biophysical features and spectral characteristics of plantations will be introduced first, a comparison on existing algorithms in terms of different plantation types. Based on that, we proposed potential improvements in large scale plantation mapping based on the virtual constellation of multiple sensors, citizen science tools, and cloud computing technology. Based on the literature review, we discussed a series of issues for future scale operational paddy rice mapping.

Transfer Learning for Improved Audio-Based Human Activity Recognition.

PubMed

Ntalampiras, Stavros; Potamitis, Ilyas

2018-06-25

Human activities are accompanied by characteristic sound events, the processing of which might provide valuable information for automated human activity recognition. This paper presents a novel approach addressing the case where one or more human activities are associated with limited audio data, resulting in a potentially highly imbalanced dataset. Data augmentation is based on transfer learning; more specifically, the proposed method: (a) identifies the classes which are statistically close to the ones associated with limited data; (b) learns a multiple input, multiple output transformation; and (c) transforms the data of the closest classes so that it can be used for modeling the ones associated with limited data. Furthermore, the proposed framework includes a feature set extracted out of signal representations of diverse domains, i.e., temporal, spectral, and wavelet. Extensive experiments demonstrate the relevance of the proposed data augmentation approach under a variety of generative recognition schemes.

Temperature dependent BRDF facility

NASA Astrophysics Data System (ADS)

Airola, Marc B.; Brown, Andrea M.; Hahn, Daniel V.; Thomas, Michael E.; Congdon, Elizabeth A.; Mehoke, Douglas S.

2014-09-01

Applications involving space based instrumentation and aerodynamically heated surfaces often require knowledge of the bi-directional reflectance distribution function (BRDF) of an exposed surface at high temperature. Addressing this need, the Johns Hopkins University Applied Physics Laboratory (JHU/APL) developed a BRDF facility that features a multiple-port vacuum chamber, multiple laser sources covering the spectral range from the longwave infrared to the ultraviolet, imaging pyrometry and laser heated samples. Laser heating eliminates stray light that would otherwise be seen from a furnace and requires minimal sample support structure, allowing low thermal conduction loss to be obtained, which is especially important at high temperatures. The goal is to measure the BRDF of ceramic-coated surfaces at temperatures in excess of 1000°C in a low background environment. Most ceramic samples are near blackbody in the longwave infrared, thus pyrometry using a LWIR camera can be very effective and accurate.

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

Identification of different coordination geometries by XAFS in copper(II) complexes with trimesic acid

NASA Astrophysics Data System (ADS)

Gaur, A.; Klysubun, W.; Soni, Balram; Shrivastava, B. D.; Prasad, J.; Srivastava, K.

2016-10-01

X-ray absorption spectroscopy (XAS) is very useful in revealing the information about geometric and electronic structure of a transition-metal absorber and thus commonly used for determination of metal-ligand coordination. But XAFS analysis becomes difficult if differently coordinated metal centers are present in a system. In the present investigation, existence of distinct coordination geometries around metal centres have been studied by XAFS in a series of trimesic acid Cu(II) complexes. The complexes studied are: Cu3(tma)2(im)6 8H2O (1), Cu3(tma)2(mim)6 17H2O (2), Cu3(tma)2(tmen)3 8.5H2O (3), Cu3(tma) (pmd)3 6H2O (ClO4)3 (4) and Cu3(tma)2 3H2O (5). These complexes have not only Cu metal centres with different coordination but in complexes 1-3, there are multiple coordination geometries present around Cu centres. Using XANES spectra, different coordination geometries present in these complexes have been identified. The variation observed in the pre-edge features and edge features have been correlated with the distortion of the specific coordination environment around Cu centres in the complexes. XANES spectra have been calculated for the distinct metal centres present in the complexes by employing ab-initio calculations. These individual spectra have been used to resolve the spectral contribution of the Cu centres to the particular XANES features exhibited by the experimental spectra of the multinuclear complexes. Also, the variation in the 4p density of states have been calculated for the different Cu centres and then correlated with the features originated from corresponding coordination of Cu. Thus, these spectral features have been successfully utilized to detect the presence of the discrete metal centres in a system. The inferences about the coordination geometry have been supported by EXAFS analysis which has been used to determine the structural parameters for these complexes.

On the intrinsic timescales of temporal variability in measurements of the surface solar radiation

NASA Astrophysics Data System (ADS)

Bengulescu, Marc; Blanc, Philippe; Wald, Lucien

2018-01-01

This study is concerned with the intrinsic temporal scales of the variability in the surface solar irradiance (SSI). The data consist of decennial time series of daily means of the SSI obtained from high-quality measurements of the broadband solar radiation impinging on a horizontal plane at ground level, issued from different Baseline Surface Radiation Network (BSRN) ground stations around the world. First, embedded oscillations sorted in terms of increasing timescales of the data are extracted by empirical mode decomposition (EMD). Next, Hilbert spectral analysis is applied to obtain an amplitude-modulation-frequency-modulation (AM-FM) representation of the data. The time-varying nature of the characteristic timescales of variability, along with the variations in the signal intensity, are thus revealed. A novel, adaptive null hypothesis based on the general statistical characteristics of noise is employed in order to discriminate between the different features of the data, those that have a deterministic origin and those being realizations of various stochastic processes. The data have a significant spectral peak corresponding to the yearly variability cycle and feature quasi-stochastic high-frequency variability components, irrespective of the geographical location or of the local climate. Moreover, the amplitude of this latter feature is shown to be modulated by variations in the yearly cycle, which is indicative of nonlinear multiplicative cross-scale couplings. The study has possible implications on the modeling and the forecast of the surface solar radiation, by clearly discriminating the deterministic from the quasi-stochastic character of the data, at different local timescales.

Comparison of three methods for long-term monitoring of boreal lake area using Landsat TM and ETM+ imagery

USGS Publications Warehouse

Roach, Jennifer K.; Griffith, Brad; Verbyla, David

2012-01-01

Programs to monitor lake area change are becoming increasingly important in high latitude regions, and their development often requires evaluating tradeoffs among different approaches in terms of accuracy of measurement, consistency across multiple users over long time periods, and efficiency. We compared three supervised methods for lake classification from Landsat imagery (density slicing, classification trees, and feature extraction). The accuracy of lake area and number estimates was evaluated relative to high-resolution aerial photography acquired within two days of satellite overpasses. The shortwave infrared band 5 was better at separating surface water from nonwater when used alone than when combined with other spectral bands. The simplest of the three methods, density slicing, performed best overall. The classification tree method resulted in the most omission errors (approx. 2x), feature extraction resulted in the most commission errors (approx. 4x), and density slicing had the least directional bias (approx. half of the lakes with overestimated area and half of the lakes with underestimated area). Feature extraction was the least consistent across training sets (i.e., large standard error among different training sets). Density slicing was the best of the three at classifying small lakes as evidenced by its lower optimal minimum lake size criterion of 5850 m2 compared with the other methods (8550 m2). Contrary to conventional wisdom, the use of additional spectral bands and a more sophisticated method not only required additional processing effort but also had a cost in terms of the accuracy and consistency of lake classifications.

Improved P300 speller performance using electrocorticography, spectral features, and natural language processing.

PubMed

Speier, William; Fried, Itzhak; Pouratian, Nader

2013-07-01

The P300 speller is a system designed to restore communication to patients with advanced neuromuscular disorders. This study was designed to explore the potential improvement from using electrocorticography (ECoG) compared to the more traditional usage of electroencephalography (EEG). We tested the P300 speller on two epilepsy patients with temporary subdural electrode arrays over the occipital and temporal lobes respectively. We then performed offline analysis to determine the accuracy and bit rate of the system and integrated spectral features into the classifier and used a natural language processing (NLP) algorithm to further improve the results. The subject with the occipital grid achieved an accuracy of 82.77% and a bit rate of 41.02, which improved to 96.31% and 49.47 respectively using a language model and spectral features. The temporal grid patient achieved an accuracy of 59.03% and a bit rate of 18.26 with an improvement to 75.81% and 27.05 respectively using a language model and spectral features. Spatial analysis of the individual electrodes showed best performance using signals generated and recorded near the occipital pole. Using ECoG and integrating language information and spectral features can improve the bit rate of a P300 speller system. This improvement is sensitive to the electrode placement and likely depends on visually evoked potentials. This study shows that there can be an improvement in BCI performance when using ECoG, but that it is sensitive to the electrode location. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

In vivo single-shot three-dimensionally localized multiple quantum spectroscopy of GABA in the human brain with improved spectral selectivity

NASA Astrophysics Data System (ADS)

Choi, In-Young; Lee, Sang-Pil; Shen, Jun

2005-01-01

A single-shot multiple quantum filtering method is developed that uses two double-band frequency selective pulses for enhanced spectral selectivity in combination with a slice-selective 90°, a slice-selective universal rotator 90°, and a spectral-spatial pulse composed of two slice-selective universal rotator 45° pulses for single-shot three-dimensional localization. The use of this selective multiple quantum filtering method for C3 and C4 methylene protons of GABA resulted in improved spectral selectivity for GABA and effective suppression of overlapping signals such as creatine and glutathione in each single scan, providing reliable measurements of the GABA doublet in all subjects. The concentration of GABA was measured to be 0.7 ± 0.2 μmol/g (means ± SD, n = 15) in the fronto-parietal region of the human brain in vivo.

Factorization-based texture segmentation

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less

Parameterization of the Voice Source by Combining Spectral Decay and Amplitude Features of the Glottal Flow.

ERIC Educational Resources Information Center

Alku, Paavo; Vilkman, Erkki; Laukkanen, Anne-Maria

1998-01-01

A new method is presented for the parameterization of glottal volume velocity waveforms that have been estimated by inverse filtering acoustic speech pressure signals. The new technique combines two features of voice production: the AC value and the spectral decay of the glottal flow. Testing found the new parameter correlates strongly with the…

Spectral analysis of ground penetrating radar signals in concrete, metallic and plastic targets

NASA Astrophysics Data System (ADS)

Santos, Vinicius Rafael N. dos; Al-Nuaimy, Waleed; Porsani, Jorge Luís; Hirata, Nina S. Tomita; Alzubi, Hamzah S.

2014-01-01

The accuracy of detecting buried targets using ground penetrating radar (GPR) depends mainly on features that are extracted from the data. The objective of this study is to test three spectral features and evaluate the quality to provide a good discrimination among three types of materials (concrete, metallic and plastic) using the 200 MHz GPR system. The spectral features which were selected to check the interaction of the electromagnetic wave with the type of material are: the power spectral density (PSD), short-time Fourier transform (STFT) and the Wigner-Ville distribution (WVD). The analyses were performed with simulated data varying the sizes of the targets and the electrical properties (relative dielectric permittivity and electrical conductivity) of the soil. To check if the simulated data are in accordance with the real data, the same approach was applied on the data obtained in the IAG/USP test site. A noticeable difference was found in the amplitude of the studies' features in the frequency domain and these results show the strength of the signal processing to try to differentiate buried materials using GPR, and so can be used in urban planning and geotechnical studies.

Microscopic and macroscopic spectral peculiarities of cutaneous tumours

NASA Astrophysics Data System (ADS)

Borisova, Ekaterina; Genova, Tsanislava; Troyanova, Petranka; Terziev, Ivan; Zakharov, Valery; Bratchenko, Ivan; Lomova, Maria; Gorin, Dmitry; Avramov, Latchezar

2017-12-01

Autofluorescence spectral and confocal microscopic measurements were made on different cutaneous neoplastic lesions, namely basal cell carcinoma, squamous cell carcinoma, malignant melanoma, and their dysplastic forms - keratoacantoma, dysplastic nevi and benign lesions related - basal cell papiloma, seboreic keratosa and compound nevi using excitation at 405 nm. Spectroscopic investigations were made on in vivo and ex vivo tissue samples, and confocal microscopy investigations were made on ex vivo and eosin-haematoxilin stained thin slices of the tumours detected. Correlation between the spectral data received and the microscopic features observed was found, related to the morphological and biochemical alterations during neoplasia growth. Specific spectral features observed in each type of lesion investigated on micro and macro level would be presented and discussed.

Spectral lags in different episodes of gamma-ray bursts

NASA Astrophysics Data System (ADS)

Jia, LanWei; Yi, TingFeng; Liang, EnWei

2013-08-01

A systematical analysis of the spectral lags in different episodes within a gamma-ray burst (GRB) for the BATSE GRB sample is given. The identified episodes are usually a single pulse with mixing of small fluctuations. The spectral lags were calculated for lightcurves in the 25-55 keV and 110-320 keV bands. No universal spectral lag evolution feature in different episodes within a GRB were found for most GRBs. Among 362 bright GRBs that have at least three well-identified episodes, 19 of them show long-to-short lag and 19 of them show short-to-long lag in successive episodes. The other 324 GRBs have no clear evolution trend. Defining the specified lag with the ratio of the spectral lag to the episode duration in 110-320 keV band, no prominent case of specified lag was found showing clear evolution features. The results suggest that the observed spectral lag may contribute to the dynamics and/or the radiation physics of a given emission episode.

Near-infrared spectral reflectance of mineral mixtures - Systematic combinations of pyroxenes, olivine, and iron oxides

NASA Technical Reports Server (NTRS)

Singer, R. B.

1981-01-01

Near-infrared spectral reflectance data are presented for systematic variations in weight percent of two component mixtures of ferromagnesium and iron oxide minerals used to study the dark materials on Mars. Olivine spectral features are greatly reduced in contrast by admixture of other phases but remain distinctive even for low olivine contents. Clinopyroxene and orthopyroxene mixtures show resolved pyroxene absorptions near 2 microns. Limonite greatly modifies pyroxene and olivine reflectance, but does not fully eliminate distinctive spectral characteristics. Using only spectral data in the 1 micron region, it is difficult to differentiate orthopyroxene and limonite in a mixture. All composite mineral absorptions were either weaker than or intermediate in strength to the end-member absorptions and have bandwidths greater than or equal to those for the end members. In general, spectral properties in an intimate mixture combine in a complex, nonadditive manner, with features demonstrating a regular but usually nonlinear variation as a function of end-member phase proportions.

High-angular-resolution stellar imaging with occultations from the Cassini spacecraft - III. Mira

NASA Astrophysics Data System (ADS)

Stewart, Paul N.; Tuthill, Peter G.; Nicholson, Philip D.; Hedman, Matthew M.

2016-04-01

We present an analysis of spectral and spatial data of Mira obtained by the Cassini spacecraft, which not only observed the star's spectra over a broad range of near-infrared wavelengths, but was also able to obtain high-resolution spatial information by watching the star pass behind Saturn's rings. The observed spectral range of 1-5 microns reveals the stellar atmosphere in the crucial water-bands which are unavailable to terrestrial observers, and the simultaneous spatial sampling allows the origin of spectral features to be located in the stellar environment. Models are fitted to the data, revealing the spectral and spatial structure of molecular layers surrounding the star. High-resolution imagery is recovered revealing the layered and asymmetric nature of the stellar atmosphere. The observational data set is also used to confront the state-of-the-art cool opacity-sampling dynamic extended atmosphere models of Mira variables through a detailed spectral and spatial comparison, revealing in general a good agreement with some specific departures corresponding to particular spectral features.

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Single-molecule spectroscopy unmasks the lowest exciton state of the B850 assembly in LH2 from Rps. acidophila.

PubMed

Kunz, Ralf; Timpmann, Kõu; Southall, June; Cogdell, Richard J; Freiberg, Arvi; Köhler, Jürgen

2014-05-06

We have recorded fluorescence-excitation and emission spectra from single LH2 complexes from Rhodopseudomonas (Rps.) acidophila. Both types of spectra show strong temporal spectral fluctuations that can be visualized as spectral diffusion plots. Comparison of the excitation and emission spectra reveals that for most of the complexes the lowest exciton transition is not observable in the excitation spectra due to the cutoff of the detection filter characteristics. However, from the spectral diffusion plots we have the full spectral and temporal information at hand and can select those complexes for which the excitation spectra are complete. Correlating the red most spectral feature of the excitation spectrum with the blue most spectral feature of the emission spectrum allows an unambiguous assignment of the lowest exciton state. Hence, application of fluorescence-excitation and emission spectroscopy on the same individual LH2 complex allows us to decipher spectral subtleties that are usually hidden in traditional ensemble spectroscopy. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Biologically-inspired data decorrelation for hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Picon, Artzai; Ghita, Ovidiu; Rodriguez-Vaamonde, Sergio; Iriondo, Pedro Ma; Whelan, Paul F.

2011-12-01

Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

Going Deeper With Contextual CNN for Hyperspectral Image Classification.

PubMed

Lee, Hyungtae; Kwon, Heesung

2017-10-01

In this paper, we describe a novel deep convolutional neural network (CNN) that is deeper and wider than other existing deep networks for hyperspectral image classification. Unlike current state-of-the-art approaches in CNN-based hyperspectral image classification, the proposed network, called contextual deep CNN, can optimally explore local contextual interactions by jointly exploiting local spatio-spectral relationships of neighboring individual pixel vectors. The joint exploitation of the spatio-spectral information is achieved by a multi-scale convolutional filter bank used as an initial component of the proposed CNN pipeline. The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map. The joint feature map representing rich spectral and spatial properties of the hyperspectral image is then fed through a fully convolutional network that eventually predicts the corresponding label of each pixel vector. The proposed approach is tested on three benchmark data sets: the Indian Pines data set, the Salinas data set, and the University of Pavia data set. Performance comparison shows enhanced classification performance of the proposed approach over the current state-of-the-art on the three data sets.

Location of γ-ray emission and magnetic field strengths in OJ 287

NASA Astrophysics Data System (ADS)

Hodgson, J. A.; Krichbaum, T. P.; Marscher, A. P.; Jorstad, S. G.; Rani, B.; Marti-Vidal, I.; Bach, U.; Sanchez, S.; Bremer, M.; Lindqvist, M.; Uunila, M.; Kallunki, J.; Vicente, P.; Fuhrmann, L.; Angelakis, E.; Karamanavis, V.; Myserlis, I.; Nestoras, I.; Chidiac, C.; Sievers, A.; Gurwell, M.; Zensus, J. A.

2017-01-01

Context. The γ-ray BL Lac object OJ 287 is known to exhibit inner-parsec "jet-wobbling", high degrees of variability at all wavelengths and quasi-stationary features, including an apparent (≈100°) position-angle change in projection on the sky plane. Aims: Sub-50 micro-arcsecond resolution 86 GHz observations with the global mm-VLBI array (GMVA) supplement ongoing multi-frequency VLBI blazar monitoring at lower frequencies. Using these maps, together with cm/mm total intensity and γ-ray observations from Fermi-LAT from 2008-2014, we aim to determine the location of γ-ray emission and to explain the inner-mas structural changes. Methods: Observations with the GMVA offer approximately double the angular resolution compared with 43 GHz VLBA observations and enable us to observe above the synchrotron self-absorption peak frequency. Fermi-LAT γ-ray data were reduced and analysed. The jet was spectrally decomposed at multiple locations along the jet. From this, we could derive estimates of the magnetic field using equipartition and synchrotron self-absorption arguments. How the field decreases down the jet provided an estimate of the distance to the jet apex and an estimate of the magnetic field strength at the jet apex and in the broad line region. Combined with accurate kinematics, we attempt to locate the site of γ-ray activity, radio flares, and spectral changes. Results: Strong γ-ray flares appeared to originate from either the so-called core region, a downstream stationary feature, or both, with γ-ray activity significantly correlated with radio flaring in the downstream quasi-stationary feature. Magnetic field estimates were determined at multiple locations along the jet, with the magnetic field found to be ≥1.6 G in the core and ≤0.4 G in the downstream quasi-stationary feature. We therefore found upper limits on the location of the VLBI core as ≲6.0 pc from the jet apex and determined an upper limit on the magnetic field near the jet base of the order of thousands of Gauss. The 3 mm GMVA data are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/597/A80

Using Differential Evolution to Optimize Learning from Signals and Enhance Network Security

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harmer, Paul K; Temple, Michael A; Buckner, Mark A

2011-01-01

Computer and communication network attacks are commonly orchestrated through Wireless Access Points (WAPs). This paper summarizes proof-of-concept research activity aimed at developing a physical layer Radio Frequency (RF) air monitoring capability to limit unauthorizedWAP access and mprove network security. This is done using Differential Evolution (DE) to optimize the performance of a Learning from Signals (LFS) classifier implemented with RF Distinct Native Attribute (RF-DNA) fingerprints. Performance of the resultant DE-optimized LFS classifier is demonstrated using 802.11a WiFi devices under the most challenging conditions of intra-manufacturer classification, i.e., using emissions of like-model devices that only differ in serial number. Using identicalmore » classifier input features, performance of the DE-optimized LFS classifier is assessed relative to a Multiple Discriminant Analysis / Maximum Likelihood (MDA/ML) classifier that has been used for previous demonstrations. The comparative assessment is made using both Time Domain (TD) and Spectral Domain (SD) fingerprint features. For all combinations of classifier type, feature type, and signal-to-noise ratio considered, results show that the DEoptimized LFS classifier with TD features is uperior and provides up to 20% improvement in classification accuracy with proper selection of DE parameters.« less

First results of the observations of trace gases in the Martian atmosphere by the Planetary Fourier Spectrometer onboard the Mars Express

NASA Astrophysics Data System (ADS)

Titov, D. V.; Ignatiev, N.; Formisano, V.; Grassi, D.; Giuranna, M.; Maturilli, A.; Piccioni, G.; Moroz, V. I.; Lellouch, E.; Encrenaz, T.; Pfs Team

High spectral resolution observations of Mars by the PFS/Mars Express provide new insight into the atmospheric composition. Spectral features of atmospheric CO2 and its isotopes at 15, 4.3, 2.7, 1.4 μ m, CO at 4.7 and 2.35 μ m, and H2O at 40, 2.56, and 1.38 μ m as well as solar spectral features are clearly identified in the PFS spectra. HDO spectral details at 3.7 μ m were also tentatively detected. The paper will present qualitative and quantitative analysis of the PFS spectra in the regions of spectral bands of trace gases. Abundance of minor constituents will be determined using complete radiative transfer modeling including possible non-LTE effects. We will also present results of search for other minor species with emphasis on the limb observations that provide higher air mass factor.

Space-Weathered Anorthosite as Spectral D-Type Material on the Martian Satellites

NASA Astrophysics Data System (ADS)

Yamamoto, S.; Watanabe, S.; Matsunaga, T.

2018-02-01

Spectral D-type asteroids are characterized by dark, red-sloped, and featureless spectra at visible and near-infrared wavelengths and are thought to be composed of rocks rich in organic compounds. The Martian satellites, Phobos and Deimos, spectrally resemble D-type asteroids, suggesting that they are captured D-type asteroids from outside the Martian system. Here we show that the spectral features of lunar space-weathered anorthosite are consistent with D-type spectra, including those of Phobos and Deimos. This can also explain the distinct spectral features on Phobos, the red and blue units, as arising from different degrees of space weathering. Thus, D-type spectra of the Martian satellites can be explained by space-weathered anorthosite, indicating that D-type spectra do not necessarily support the existence of organic compounds, which would be strong evidence for the capture scenario.

The ArF laser for the next-generation multiple-patterning immersion lithography supporting green operations

NASA Astrophysics Data System (ADS)

Ishida, Keisuke; Ohta, Takeshi; Miyamoto, Hirotaka; Kumazaki, Takahito; Tsushima, Hiroaki; Kurosu, Akihiko; Matsunaga, Takashi; Mizoguchi, Hakaru

2016-03-01

Multiple patterning ArF immersion lithography has been expected as the promising technology to satisfy tighter leading edge device requirements. One of the most important features of the next generation lasers will be the ability to support green operations while further improving cost of ownership and performance. Especially, the dependence on rare gases, such as Neon and Helium, is becoming a critical issue for high volume manufacturing process. The new ArF excimer laser, GT64A has been developed to cope with the reduction of operational costs, the prevention against rare resource shortage and the improvement of device yield in multiple-patterning lithography. GT64A has advantages in efficiency and stability based on the field-proven injection-lock twin-chamber platform (GigaTwin platform). By the combination of GigaTwin platform and the advanced gas control algorithm, the consumption of rare gases such as Neon is reduced to a half. And newly designed Line Narrowing Module can realize completely Helium free operation. For the device yield improvement, spectral bandwidth stability is important to increase image contrast and contribute to the further reduction of CD variation. The new spectral bandwidth control algorithm and high response actuator has been developed to compensate the offset due to thermal change during the interval such as the period of wafer exchange operation. And REDeeM Cloud™, new monitoring system for managing light source performance and operations, is on-board and provides detailed light source information such as wavelength, energy, E95, etc.

Spectral Mapping at Asteroid 101955 Bennu

NASA Astrophysics Data System (ADS)

Clark, Beth Ellen; Hamilton, Victoria E.; Emery, Joshua P.; Hawley, C. Luke; Howell, Ellen S.; Lauretta, Dante; Simon, Amy A.; Christensen, Philip R.; Reuter, Dennis

2017-10-01

The OSIRIS-REx Asteroid Sample Return mission was launched in September 2016. The main science surveys of asteroid 101955 Bennu start in March 2019. Science instruments include a Visible-InfraRed Spectrometer (OVIRS) and a Thermal Emission Spectrometer (OTES) that will produce observations that will be co-registered to the tessellated shape model of Bennu (the fundamental unit of which is a triangular facet). One task of the science team is to synthesize the results in real time during proximity operations to contribute to selection of the sampling site. Hence, we will be focused on quickly producing spectral maps for: (1) mineral abundances; (2) band strengths of minerals and chemicals (including a search for the subtle ~5% absorption feature produced by organics in meteorites); and (3) temperature and thermal inertia values. In sum, we will be producing on the order of ~60 spectral maps of Bennu’s surface composition and thermophysical properties. Due to overlapping surface spots, simulations of our spectral maps show there may be an opportunity to perform spectral super-resolution. We have a large parameter space of choices available in creating spectral maps of Bennu, including: (a) mean facet size (shape model resolution), (b) percentage of overlap between subsequent spot measurements, (c) the number of spectral spots measured per facet, and (d) the mathematical algorithm used to combine the overlapping spots (or bin them on a per-facet basis). Projection effects -- caused by irregular sampling of an irregularly shaped object with circular spectrometer fields-of-view and then mapping these circles onto triangular facets -- can be intense. To prepare for prox ops, we are simulating multiple mineralogical “truth worlds” of Bennu to study the projection effects that result from our planned methods of spectral mapping. This presentation addresses: Can we combine the three planned global surveys of the asteroid (to be obtained at different phase angles) to create a spectral map with higher spatial resolution than the native spectrometer field-of-view in order to increase our confidence in detection of a spatially small occurrence of organics on Bennu?

Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis

NASA Astrophysics Data System (ADS)

Li, Hai; Kumavor, Patrick; Salman Alqasemi, Umar; Zhu, Quing

2015-01-01

A composite set of ovarian tissue features extracted from photoacoustic spectral data, beam envelope, and co-registered ultrasound and photoacoustic images are used to characterize malignant and normal ovaries using logistic and support vector machine (SVM) classifiers. Normalized power spectra were calculated from the Fourier transform of the photoacoustic beamformed data, from which the spectral slopes and 0-MHz intercepts were extracted. Five features were extracted from the beam envelope and another 10 features were extracted from the photoacoustic images. These 17 features were ranked by their p-values from t-tests on which a filter type of feature selection method was used to determine the optimal feature number for final classification. A total of 169 samples from 19 ex vivo ovaries were randomly distributed into training and testing groups. Both classifiers achieved a minimum value of the mean misclassification error when the seven features with lowest p-values were selected. Using these seven features, the logistic and SVM classifiers obtained sensitivities of 96.39±3.35% and 97.82±2.26%, and specificities of 98.92±1.39% and 100%, respectively, for the training group. For the testing group, logistic and SVM classifiers achieved sensitivities of 92.71±3.55% and 92.64±3.27%, and specificities of 87.52±8.78% and 98.49±2.05%, respectively.

Coherent Synchrotron Radiation in Laboratory Accelerators and the Double-Spectral Feature in Solar Flares

NASA Astrophysics Data System (ADS)

Cruz, Wellington; Szpigel, Sérgio; Kaufmann, Pierre; Raulin, Jean-Pierre; Klopf, Michael

2017-10-01

Recent observations of solar flares at high-frequencies have provided evidence of a new spectral component with fluxes increasing with frequency in the sub-THz to THz range. This new component occurs simultaneously but is separated from the well-known microwave spectral component that maximizes at frequencies of a few to tens of GHz. The aim of this work is to study in detail a mechanism recently suggested to describe the double-spectrum feature observed in solar flares based on the physical process known as microbunching instability, which occurs with high-energy electron beams in laboratory accelerators.

Multispectral atmospheric mapping sensor of mesoscale water vapor features

NASA Technical Reports Server (NTRS)

Menzel, P.; Jedlovec, G.; Wilson, G.; Atkinson, R.; Smith, W.

1985-01-01

The Multispectral atmospheric mapping sensor was checked out for specified spectral response and detector noise performance in the eight visible and three infrared (6.7, 11.2, 12.7 micron) spectral bands. A calibration algorithm was implemented for the infrared detectors. Engineering checkout flights on board the ER-2 produced imagery at 50 m resolution in which water vapor features in the 6.7 micron spectral band are most striking. These images were analyzed on the Man computer Interactive Data Access System (McIDAS). Ground truth and ancillary data was accessed to verify the calibration.

Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis

NASA Astrophysics Data System (ADS)

Cheng, Tao; Rivard, Benoit; Sánchez-Azofeifa, Arturo G.; Féret, Jean-Baptiste; Jacquemoud, Stéphane; Ustin, Susan L.

2014-01-01

Leaf mass per area (LMA), the ratio of leaf dry mass to leaf area, is a trait of central importance to the understanding of plant light capture and carbon gain. It can be estimated from leaf reflectance spectroscopy in the infrared region, by making use of information about the absorption features of dry matter. This study reports on the application of continuous wavelet analysis (CWA) to the estimation of LMA across a wide range of plant species. We compiled a large database of leaf reflectance spectra acquired within the framework of three independent measurement campaigns (ANGERS, LOPEX and PANAMA) and generated a simulated database using the PROSPECT leaf optical properties model. CWA was applied to the measured and simulated databases to extract wavelet features that correlate with LMA. These features were assessed in terms of predictive capability and robustness while transferring predictive models from the simulated database to the measured database. The assessment was also conducted with two existing spectral indices, namely the Normalized Dry Matter Index (NDMI) and the Normalized Difference index for LMA (NDLMA). Five common wavelet features were determined from the two databases, which showed significant correlations with LMA (R2: 0.51-0.82, p < 0.0001). The best robustness (R2 = 0.74, RMSE = 18.97 g/m2 and Bias = 0.12 g/m2) was obtained using a combination of two low-scale features (1639 nm, scale 4) and (2133 nm, scale 5), the first being predominantly important. The transferability of the wavelet-based predictive model to the whole measured database was either better than or comparable to those based on spectral indices. Additionally, only the wavelet-based model showed consistent predictive capabilities among the three measured data sets. In comparison, the models based on spectral indices were sensitive to site-specific data sets. Integrating the NDLMA spectral index and the two robust wavelet features improved the LMA prediction. One of the bands used by this spectral index, 1368 nm, was located in a strong atmospheric water absorption region and replacing it with the next available band (1340 nm) led to lower predictive accuracies. However, the two wavelet features were not affected by data quality in the atmospheric absorption regions and therefore showed potential for canopy-level investigations. The wavelet approach provides a different perspective into spectral responses to LMA variation than the traditional spectral indices and holds greater promise for implementation with airborne or spaceborne imaging spectroscopy data for mapping canopy foliar dry biomass.

Active listening: task-dependent plasticity of spectrotemporal receptive fields in primary auditory cortex.

PubMed

Fritz, Jonathan; Elhilali, Mounya; Shamma, Shihab

2005-08-01

Listening is an active process in which attentive focus on salient acoustic features in auditory tasks can influence receptive field properties of cortical neurons. Recent studies showing rapid task-related changes in neuronal spectrotemporal receptive fields (STRFs) in primary auditory cortex of the behaving ferret are reviewed in the context of current research on cortical plasticity. Ferrets were trained on spectral tasks, including tone detection and two-tone discrimination, and on temporal tasks, including gap detection and click-rate discrimination. STRF changes could be measured on-line during task performance and occurred within minutes of task onset. During spectral tasks, there were specific spectral changes (enhanced response to tonal target frequency in tone detection and discrimination, suppressed response to tonal reference frequency in tone discrimination). However, only in the temporal tasks, the STRF was changed along the temporal dimension by sharpening temporal dynamics. In ferrets trained on multiple tasks, distinctive and task-specific STRF changes could be observed in the same cortical neurons in successive behavioral sessions. These results suggest that rapid task-related plasticity is an ongoing process that occurs at a network and single unit level as the animal switches between different tasks and dynamically adapts cortical STRFs in response to changing acoustic demands.

Multi-contrast light profile microscopy for the depth-resolved imaging of the properties of multi-ply thin films.

PubMed

Power, J F

2009-06-01

Light profile microscopy (LPM) is a direct method for the spectral depth imaging of thin film cross-sections on the micrometer scale. LPM uses a perpendicular viewing configuration that directly images a source beam propagated through a thin film. Images are formed in dark field contrast, which is highly sensitive to subtle interfacial structures that are invisible to reference methods. The independent focusing of illumination and imaging systems allows multiple registered optical sources to be hosted on a single platform. These features make LPM a powerful multi-contrast (MC) imaging technique, demonstrated in this work with six modes of imaging in a single instrument, based on (1) broad-band elastic scatter; (2) laser excited wideband luminescence; (3) coherent elastic scatter; (4) Raman scatter (three channels with RGB illumination); (5) wavelength resolved luminescence; and (6) spectral broadband scatter, resolved in immediate succession. MC-LPM integrates Raman images with a wider optical and morphological picture of the sample than prior art microprobes. Currently, MC-LPM resolves images at an effective spectral resolution better than 9 cm(-1), at a spatial resolution approaching 1 microm, with optics that operate in air at half the maximum numerical aperture of the prior art microprobes.

Littoral assessment of mine burial signatures (LAMBS): buried landmine/background spectral-signature analyses

NASA Astrophysics Data System (ADS)

Kenton, Arthur C.; Geci, Duane M.; Ray, Kristofer J.; Thomas, Clayton M.; Salisbury, John W.; Mars, John C.; Crowley, James K.; Witherspoon, Ned H.; Holloway, John H., Jr.

2004-09-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 μm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites. We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

A linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Goetz, Alexander F. H.

1992-01-01

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described.

Littoral Assessment of Mine Burial Signatures (LAMBS) buried land mine/background spectral signature analyses

USGS Publications Warehouse

Kenton, A.C.; Geci, D.M.; Ray, K.J.; Thomas, C.M.; Salisbury, J.W.; Mars, J.C.; Crowley, J.K.; Witherspoon, N.H.; Holloway, J.H.; Harmon R.S.Broach J.T.Holloway, Jr. J.H.

2004-01-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 ??m) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites.1 We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

Examining spectral variations in localized lunar dark mantle deposits

USGS Publications Warehouse

Jawin, Erica; Besse, Sebastien; Gaddis, Lisa R.; Sunshine, Jessica; Head, James W.; Mazrouei, Sara

2015-01-01

The localized lunar dark mantle deposits (DMDs) in Alphonsus, J. Herschel, and Oppenheimer craters were analyzed using visible-near-infrared spectroscopy data from the Moon Mineralogy Mapper. Spectra of these localized DMDs were analyzed for compositional and mineralogical variations within the deposits and were compared with nearby mare basalt units. Spectra of the three localized DMDs exhibited mafic absorption features indicating iron-rich compositions, although the DMDs were spectrally distinct from nearby mare basalts. All of the DMDs contained spectral signatures of glassy materials, suggesting the presence of volcanic glass in varying concentrations across the individual deposits. In addition, the albedo and spectral signatures were variable within the Alphonsus and Oppenheimer crater DMDs, suggesting variable deposit thickness and/or variations in the amount of mixing with the local substrate. Two previously unidentified localized DMDs were discovered to the northeast of Oppenheimer crater. The identification of high concentrations of volcanic glass in multiple localized DMDs in different locations suggests that the distribution of volcanic glass across the lunar surface is much more widespread than has been previously documented. The presence of volcanic glass implies an explosive, vulcanian eruption style for localized DMDs, as this allows volcanic glass to rapidly quench, inhibiting crystallization, compared to the larger hawaiian-style eruptions typical of regional DMD emplacement where black beads indicate a higher degree of crystallization. Improved understanding of the local and global distributions of volcanic glass in lunar DMDs will further constrain lunar degassing and compositional evolution throughout lunar volcanic history.

Lithographic VCSEL array multimode and single mode sources for sensing and 3D imaging

NASA Astrophysics Data System (ADS)

Leshin, J.; Li, M.; Beadsworth, J.; Yang, X.; Zhang, Y.; Tucker, F.; Eifert, L.; Deppe, D. G.

2016-05-01

Sensing applications along with free space data links can benefit from advanced laser sources that produce novel radiation patterns and tight spectral control for optical filtering. Vertical-cavity surface-emitting lasers (VCSELs) are being developed for these applications. While oxide VCSELs are being produced by most companies, a new type of oxide-free VCSEL is demonstrating many advantages in beam pattern, spectral control, and reliability. These lithographic VCSELs offer increased power density from a given aperture size, and enable dense integration of high efficiency and single mode elements that improve beam pattern. In this paper we present results for lithographic VCSELs and describes integration into military systems for very low cost pulsed applications, as well as continuouswave applications in novel sensing applications. The VCSELs are being developed for U.S. Army for soldier weapon engagement simulation training to improve beam pattern and spectral control. Wavelengths in the 904 nm to 990 nm ranges are being developed with the spectral control designed to eliminate unwanted water absorption bands from the data links. Multiple beams and radiation patterns based on highly compact packages are being investigated for improved target sensing and transmission fidelity in free space data links. These novel features based on the new VCSEL sources are also expected to find applications in 3-D imaging, proximity sensing and motion control, as well as single mode sensors such as atomic clocks and high speed data transmission.

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen

2017-12-01

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.

Single trial decoding of belief decision making from EEG and fMRI data using independent components features

PubMed Central

Douglas, Pamela K.; Lau, Edward; Anderson, Ariana; Head, Austin; Kerr, Wesley; Wollner, Margalit; Moyer, Daniel; Li, Wei; Durnhofer, Mike; Bramen, Jennifer; Cohen, Mark S.

2013-01-01

The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject's decision response to a given propositional statement based on independent component (IC) features derived from EEG and fMRI data. Our results demonstrate that IC features outperformed features derived from event related spectral perturbations derived from any single spectral band, yet were similar to accuracy across all spectral bands combined. We compared our diagnostic IC spatial maps with our conventional general linear model (GLM) results, and found that informative ICs had significant spatial overlap with our GLM results, yet also revealed unique regions like amygdala that were not statistically significant in GLM analyses. Overall, these results suggest that ICs may yield a parsimonious feature set that can be used along with a decision tree structure for interpretation of features used in classifying complex cognitive processes such as belief and disbelief across both fMRI and EEG neuroimaging modalities. PMID:23914164

Predicting Upwelling Radiance on the West Florida Shelf

DTIC Science & Technology

2006-03-31

National Science Foundation . The chemical and biological model includes the ability to simulate multiple groups of phytoplankton, multiple limiting nutrients, spectral light harvesting by phytoplankton, multiple particulate and dissolved degradational pools of organic material, and non-stoichometric carbon, nitrogen, phosphorus, silica, and iron dynamics. It also includes a complete spectral light model for the prediction of Inherent Optical Properties (IOPs). The coupling of the predicted IOP model (Ecosim 2.0) with robust radiative transfer model (Ecolight

Is Tridymite at Gale Crater Evidence for Silicic Volcanism on Mars?

NASA Technical Reports Server (NTRS)

Morris, Richard V.; Vaniman, David T.; Ming, Douglas W.; Graff, Trevor G.; Downs, Robert T.; Fendrich, Kim; Mertzman, Stanley A.

2016-01-01

The X-ray diffraction (XRD) instrument (CheMin) onboard the MSL rover Curiosity detected 17 wt% of the SiO2 polymorph tridymite (relative to bulk sample) for the Buckskin drill sample (73 wt% SiO2) obtained from sedimentary rock in the Murray formation at Gale Crater, Mars. Other detected crystalline materials are plagioclase, sanidine, cristobalite, cation-deficient magnetite, and anhydrite. XRD amorphous material constitutes approx. 60 wt% of bulk sample, and the position of its broad diffraction peak near approx. 26 deg. 2-theta is consistent with opal-A. Tridymite is a lowpressure, high-temperature mineral (approx. 870 to 1670 deg. C) whose XRD-identified occurrence on the Earth is usually associated with silicic (e.g., rhyolitic) volcanism. High SiO2 deposits have been detected at Gale crater by remote sensing from martian orbit and interpreted as opal-A on the basis H2O and Si-OH spectral features. Proposed opal-A formation pathways include precipitation of silica from lake waters and high-SiO2 residues of acid-sulfate leaching. Tridymite is nominally anhydrous and would not exhibit these spectral features. We have chemically and spectrally analyzed rhyolitic samples from New Mexico and Iwodake volcano (Japan). The glassy (by XRD) NM samples have H2O spectral features similar to opal-A. The Iwodake sample, which has been subjected to high-temperature acid sulfate leaching, also has H2O spectral features similar to opal-A. The Iwodake sample has approx. 98 wt% SiO2 and 1% wt% TiO2 (by XRF), tridymite (>80 wt.% of crystalline material without detectable quartz by XRD), and H2O and Si-OH spectral features. These results open the working hypothesis that the opal-A-like high-SiO2 deposits at Gale crater detected from martian orbit are products of alteration associated with silicic volcanism. The presence or absence of tridymite will depend on lava crystallization temperatures (NM) and post crystallization alteration temperatures (Iwodake).

EDA-gram: designing electrodermal activity fingerprints for visualization and feature extraction.

PubMed

Chaspari, Theodora; Tsiartas, Andreas; Stein Duker, Leah I; Cermak, Sharon A; Narayanan, Shrikanth S

2016-08-01

Wearable technology permeates every aspect of our daily life increasing the need of reliable and interpretable models for processing the large amount of biomedical data. We propose the EDA-Gram, a multidimensional fingerprint of the electrodermal activity (EDA) signal, inspired by the widely-used notion of spectrogram. The EDA-Gram is based on the sparse decomposition of EDA from a knowledge-driven set of dictionary atoms. The time axis reflects the analysis frames, the spectral dimension depicts the width of selected dictionary atoms, while intensity values are computed from the atom coefficients. In this way, EDA-Gram incorporates the amplitude and shape of Skin Conductance Responses (SCR), which comprise an essential part of the signal. EDA-Gram is further used as a foundation for signal-specific feature design. Our results indicate that the proposed representation can accentuate fine-grain signal fluctuations, which might not always be apparent through simple visual inspection. Statistical analysis and classification/regression experiments further suggest that the derived features can differentiate between multiple arousal levels and stress-eliciting environments for two datasets.

Spectral Measurements of Geosynchronous Satellites During Glint Season

DTIC Science & Technology

2015-01-01

the satellite solar panels and has been observed in the past using broadband photometry techniques. In this paper, we present the first observations... photometry . We believe that these small-scale features can be exploited to discern satellite features such as solar panel orientation and secondary...Spectral Measurements of Geosynchronous Satellites During Glint Season Ryan M. Tucker, Evan M. Weld, Francis K. Chun, and Roger D. Tippets

Algorithmic Foundation of Spectral Rarefaction for Measuring Satellite Imagery Heterogeneity at Multiple Spatial Scales

PubMed Central

Rocchini, Duccio

2009-01-01

Measuring heterogeneity in satellite imagery is an important task to deal with. Most measures of spectral diversity have been based on Shannon Information theory. However, this approach does not inherently address different scales, ranging from local (hereafter referred to alpha diversity) to global scales (gamma diversity). The aim of this paper is to propose a method for measuring spectral heterogeneity at multiple scales based on rarefaction curves. An algorithmic solution of rarefaction applied to image pixel values (Digital Numbers, DNs) is provided and discussed. PMID:22389600

Quality assessment of remote sensing image fusion using feature-based fourth-order correlation coefficient

NASA Astrophysics Data System (ADS)

Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

2016-04-01

In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.

Hyperspectral data mining to identify relevant canopy spectral features for estimating durum wheat growth, nitrogen status, and yield

USDA-ARS?s Scientific Manuscript database

Modern hyperspectral sensors permit reflectance measurements of crop canopies in hundreds of narrow spectral wavebands. While these sensors describe plant canopy reflectance in greater detail than multispectral sensors, they also suffer from issues with data redundancy and spectral autocorrelation. ...

Performance enhancement of optical code-division multiple-access systems using transposed modified Walsh code

NASA Astrophysics Data System (ADS)

Sikder, Somali; Ghosh, Shila

2018-02-01

This paper presents the construction of unipolar transposed modified Walsh code (TMWC) and analysis of its performance in optical code-division multiple-access (OCDMA) systems. Specifically, the signal-to-noise ratio, bit error rate (BER), cardinality, and spectral efficiency were investigated. The theoretical analysis demonstrated that the wavelength-hopping time-spreading system using TMWC was robust against multiple-access interference and more spectrally efficient than systems using other existing OCDMA codes. In particular, the spectral efficiency was calculated to be 1.0370 when TMWC of weight 3 was employed. The BER and eye pattern for the designed TMWC were also successfully obtained using OptiSystem simulation software. The results indicate that the proposed code design is promising for enhancing network capacity.

Identification of spectrally similar materials using the USGS Tetracorder algorithm: The calcite-epidote-chlorite problem

USGS Publications Warehouse

Dalton, J.B.; Bove, D.J.; Mladinich, C.S.; Rockwell, B.W.

2004-01-01

A scheme to discriminate and identify materials having overlapping spectral absorption features has been developed and tested based on the U.S. Geological Survey (USGS) Tetracorder system. The scheme has been applied to remotely sensed imaging spectroscopy data acquired by the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument. This approach was used to identify the minerals calcite, epidote, and chlorite in the upper Animas River watershed, Colorado. The study was motivated by the need to characterize the distribution of calcite in the watershed and assess its acid-neutralizing potential with regard to acidic mine drainage. Identification of these three minerals is difficult because their diagnostic spectral features are all centered at 2.3 ??m, and have similar shapes and widths. Previous studies overestimated calcite abundance as a result of these spectral overlaps. The use of a reference library containing synthetic mixtures of the three minerals in varying proportions was found to simplify the task of identifying these minerals when used in conjunction with a rule-based expert system. Some inaccuracies in the mineral distribution maps remain, however, due to the influence of a fourth spectral component, sericite, which exhibits spectral absorption features at 2.2 and 2.4 ??m that overlap the 2.3-??m absorption features of the other three minerals. Whereas the endmember minerals calcite, epidote, chlorite, and sericite can be identified by the method presented here, discrepancies occur in areas where all four occur together as intimate mixtures. It is expected that future work will be able to reduce these discrepancies by including reference mixtures containing sericite. ?? 2004 Elsevier Inc. All rights reserved.

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Using high spectral resolution spectrophotometry to study broad mineral absorption features on Mars

NASA Technical Reports Server (NTRS)

Blaney, D. L.; Crisp, D.

1993-01-01

Traditionally telescopic measurements of mineralogic absorption features have been made using relatively low to moderate (R=30-300) spectral resolution. Mineralogic absorption features tend to be broad so high resolution spectroscopy (R greater than 10,000) does not provide significant additional compositional information. Low to moderate resolution spectroscopy allows an observer to obtain data over a wide wavelength range (hundreds to thousands of wavenumbers) compared to the several wavenumber intervals that are collected using high resolution spectrometers. However, spectrophotometry at high resolution has major advantages over lower resolution spectroscopy in situations that are applicable to studies of the Martian surface, i.e., at wavelengths where relatively weak surface absorption features and atmospheric gas absorption features both occur.

Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data

USGS Publications Warehouse

Kokaly, Raymond F.; Despain, Don G.; Clark, Roger N.; Livo, K. Eric

2003-01-01

Knowledge of the distribution of vegetation on the landscape can be used to investigate ecosystem functioning. The sizes and movements of animal populations can be linked to resources provided by different plant species. This paper demonstrates the application of imaging spectroscopy to the study of vegetation in Yellowstone National Park (Yellowstone) using spectral feature analysis of data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data, acquired on August 7, 1996, were calibrated to surface reflectance using a radiative transfer model and field reflectance measurements of a ground calibration site. A spectral library of canopy reflectance signatures was created by averaging pixels of the calibrated AVIRIS data over areas of known forest and nonforest vegetation cover types in Yellowstone. Using continuum removal and least squares fitting algorithms in the US Geological Survey's Tetracorder expert system, the distributions of these vegetation types were determined by comparing the absorption features of vegetation in the spectral library with the spectra from the AVIRIS data. The 0.68 μm chlorophyll absorption feature and leaf water absorption features, centered near 0.98 and 1.20 μm, were analyzed. Nonforest cover types of sagebrush, grasslands, willows, sedges, and other wetland vegetation were mapped in the Lamar Valley of Yellowstone. Conifer cover types of lodgepole pine, whitebark pine, Douglas fir, and mixed Engelmann spruce/subalpine fir forests were spectrally discriminated and their distributions mapped in the AVIRIS images. In the Mount Washburn area of Yellowstone, a comparison of the AVIRIS map of forest cover types to a map derived from air photos resulted in an overall agreement of 74.1% (kappa statistic=0.62).

Ground-Based VIS/NIR Reflectance Spectra of 25143 Itokawa: What Hayabusa will See and How Ground-Based Data can Augment Analyses

NASA Technical Reports Server (NTRS)

Vilas, Faith; Abell, P. A.; Jarvis, K. S.

2004-01-01

Planning for the arrival of the Hayabusa spacecraft at asteroid 25143 Itokawa includes consideration of the expected spectral information to be obtained using the AMICA and NIRS instruments. The rotationally-resolved spatial coverage the asteroid we have obtained with ground-based telescopic spectrophotometry in the visible and near-infrared can be utilized here to address expected spacecraft data. We use spectrophotometry to simulate the types of data that Hayabusa will receive with the NIRS and AMICA instruments, and will demonstrate them here. The NIRS will cover a wavelength range from 0.85 m, and have a dispersion per element of 250 Angstroms. Thus, we are limited in coverage of the 1.0 micrometer and 2.0 micrometer mafic silicate absorption features. The ground-based reflectance spectra of Itokawa show a large component of olivine in its surface material, and the 2.0 micrometer feature is shallow. Determining the olivine to pyroxene abundance ratio is critically dependent on the attributes of the 1.0- and 2.0 micrometer features. With a cut-off near 2,1 micrometer the longer edge of the 2.0- feature will not be obtained by NIRS. Reflectance spectra obtained using ground-based telescopes can be used to determine the regional composition around space-based spectral observations, and possibly augment the longer wavelength spectral attributes. Similarly, the shorter wavelength end of the 1.0 micrometer absorption feature will be partially lost to the NIRS. The AMICA filters mimic the ECAS filters, and have wavelength coverage overlapping with the NIRS spectral range. We demonstrate how merging photometry from AMICA will extend the spectral coverage of the NIRS. Lessons learned from earlier spacecraft to asteroids should be considered.

Hyperspectral analysis of the ultramafic complex and adjacent lithologies at Mordor, NT, Australia

USGS Publications Warehouse

Rowan, L.C.; Simpson, C.J.; Mars, J.C.

2004-01-01

The Mordor Complex consists of a series of potassic ultramafic rocks which were intruded into Proterozoic felsic gneisses and amphibolite and are overlain by quartzite and unconsolidated deposits. In situ and laboratory 0.4 to 2.5 ??m reflectance spectra show Al-OH absorption features caused by absorption in muscovite, kaolinite, and illite/smectite in syenite, granitic gneiss, quartzite and unconsolidated sedimentary deposits, and Fe,Mg-OH features due to phlogopite, biotite, epidote, and hornblende in the mafic and ultramafic rocks. Ferrous-iron absorption positioned near 1.05 ??m is most intense in peridotite reflectance spectra. Ferric-iron absorption is intense in most of the felsic lithologies. HyMap data were recorded in 126 narrow bands from 0.43 to 2.5 ??m along a 7-km-wide swath with approximately 6-m spatial resolution. Correction of the data to spectral reflectance was accomplished by reference to in situ measurements of an extensive, alluvial plain. Spectral classes for matched filter processing were selected by using the pixel purity index procedure and analysis of in situ and laboratory spectra. Considering the spatial distribution of the resulting 14 classes, some classes were combined, which produced eight classes characterized by Al-OH absorption features, and three Fe,Mg-OH absorption-feature classes. Comparison of the distribution of these 11 spectral classes to a generalized lithologic map of the study area shows that the spectral distinction among the eight Al-OH classes is related to variations in primary lithology, weathering products, and vegetation density. Quartzite is represented in three classes, syenite corresponds to a single scattered class, quartz-muscovite-biotite schist defines a single very coherent class, and unconsolidated sediments are portrayed in four classes. The three mafic-ultramafic classes are distinguished on the basis of generally intense Fe,Mg-OH and ferrous-iron absorption features. A single class represents the main Mordor ultramafic mass. Epidote-bearing rocks define another class, which corresponds to biotite gneiss and, in the southern part of the area, to fracture zones. The third class, which exhibits Al-OH, as well as Fe,Mg-OH features, represents hornblende gneiss and other mafic gneisses. These results indicate the importance of analyzing the VNIR and SWIR spectral shape and albedo, as well as analyzing specific spectral features, for mapping lithologic units in this weathered terrain. ?? 2004 Elsevier Inc. All rights reserved.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

In-flight spectral performance monitoring of the Airborne Prism Experiment.

PubMed

D'Odorico, Petra; Alberti, Edoardo; Schaepman, Michael E

2010-06-01

Spectral performance of an airborne dispersive pushbroom imaging spectrometer cannot be assumed to be stable over a whole flight season given the environmental stresses present during flight. Spectral performance monitoring during flight is commonly accomplished by looking at selected absorption features present in the Sun, atmosphere, or ground, and their stability. The assessment of instrument performance in two different environments, e.g., laboratory and airborne, using precisely the same calibration reference, has not been possible so far. The Airborne Prism Experiment (APEX), an airborne dispersive pushbroom imaging spectrometer, uses an onboard in-flight characterization (IFC) facility, which makes it possible to monitor the sensor's performance in terms of spectral, radiometric, and geometric stability in flight and in the laboratory. We discuss in detail a new method for the monitoring of spectral instrument performance. The method relies on the monitoring of spectral shifts by comparing instrument-induced movements of absorption features on ground and in flight. Absorption lines originate from spectral filters, which intercept the full field of view (FOV) illuminated using an internal light source. A feature-fitting algorithm is used for the shift estimation based on Pearson's correlation coefficient. Environmental parameter monitoring, coregistered on board with the image and calibration data, revealed that differential pressure and temperature in the baffle compartment are the main driving parameters explaining the trend in spectral performance deviations in the time and the space (across-track) domains, respectively. The results presented in this paper show that the system in its current setup needs further improvements to reach a stable performance. Findings provided useful guidelines for the instrument revision currently under way. The main aim of the revision is the stabilization of the instrument for a range of temperature and pressure conditions to be encountered during operation.

Laser-induced breakdown spectroscopy (LIBS): applications in environmental issues

NASA Astrophysics Data System (ADS)

Couris, Stelios; Hatziapostolou, A.; Anglos, Dmitrios; Mavromanolakis, A.; Fotakis, Costas

1996-11-01

Results are presented from three different applications of laser induced breakdown spectroscopy (LIBS) in problems of environmental interest. In one case, LIBS is applied in the on-line control of the nickel recovery process, by monitoring the nickel content of molten ferronickel slabs, in a laboratory scale experiment. In a second case, LIBS is used in the identification of polymer materials, and on the basis of spectral features, criteria are proposed for the distinction among different types of plastic materials. Also, in preliminary experiments, the use of LIBS with respect to the detection of heavy and toxic metals in paints and the possibility of performing depth profile analysis of multiple paint layers is examined.

Multiple-path model of spectral reflectance of a dyed fabric.

PubMed

Rogers, Geoffrey; Dalloz, Nicolas; Fournel, Thierry; Hebert, Mathieu

2017-05-01

Experimental results are presented of the spectral reflectance of a dyed fabric as analyzed by a multiple-path model of reflection. The multiple-path model provides simple analytic expressions for reflection and transmission of turbid media by applying the Beer-Lambert law to each path through the medium and summing over all paths, each path weighted by its probability. The path-length probability is determined by a random-walk analysis. The experimental results presented here show excellent agreement with predictions made by the model.

Using ATR-FT/IR to detect carbohydrate-related molecular structure features of carinata meal and their in situ residues of ruminal fermentation in comparison with canola meal

NASA Astrophysics Data System (ADS)

Xin, Hangshu; Yu, Peiqiang

2013-10-01

There is no information on the co-products from carinata bio-fuel and bio-oil processing (carinata meal) in molecular structural profiles mainly related to carbohydrate biopolymers in relation to ruminant nutrition. Molecular analyses with Fourier transform infrared spectroscopy (FT/IR) technique with attenuated total reflectance (ATR) and chemometrics enable to detect structural features on a molecular basis. The objectives of this study were to: (1) determine carbohydrate conformation spectral features in original carinata meal, co-products from bio-fuel/bio-oil processing; and (2) investigate differences in carbohydrate molecular composition and functional group spectral intensities after in situ ruminal fermentation at 0, 12, 24 and 48 h compared to canola meal as a reference. The molecular spectroscopic parameters of carbohydrate profiles detected were structural carbohydrates (STCHO, mainly associated with hemi-cellulosic and cellulosic compounds; region and baseline ca. 1483-1184 cm-1), cellulosic compounds (CELC, region and baseline ca. 1304-1184 cm-1), total carbohydrates (CHO, region and baseline ca. 1193-889 cm-1) as well as the spectral ratios calculated based on respective spectral intensity data. The results showed that the spectral profiles of carinata meal were significantly different from that of canola meal in CHO 2nd peak area (center at ca. 1091 cm-1, region: 1102-1083 cm-1) and functional group peak intensity ratios such as STCHO 1st peak (ca. 1415 cm-1) to 2nd peak (ca. 1374 cm-1) height ratio, CHO 1st peak (ca. 1149 cm-1) to 3rd peak (ca. 1032 cm-1) height ratio, CELC to total CHO area ratio and STCHO to CELC area ratio, indicating that carinata meal may not in full accord with canola meal in carbohydrate utilization and availability in ruminants. Carbohydrate conformation and spectral features were changed by significant interaction of meal type and incubation time and almost all the spectral parameters were significantly decreased (P < 0.05) during 48 h ruminal degradation in both carinata meal and canola meal. Although carinata meal differed from canola meal in some carbohydrate spectral parameters, multivariate results from agglomerative hierarchical cluster analysis and principal component analysis showed that both original and in situ residues of two meals were not fully distinguished from each other within carbohydrate spectral regions. It was concluded that carbohydrate structural conformation could be detected in carinata meal by using ATR-FT/IR techniques and further study is needed to explore more information on molecular spectral features of other functional group such as protein structure profile and their association with potential nutrient supply and availability of carinata meal in animals.

Using ATR-FT/IR to detect carbohydrate-related molecular structure features of carinata meal and their in situ residues of ruminal fermentation in comparison with canola meal.

PubMed

Xin, Hangshu; Yu, Peiqiang

2013-10-01

There is no information on the co-products from carinata bio-fuel and bio-oil processing (carinata meal) in molecular structural profiles mainly related to carbohydrate biopolymers in relation to ruminant nutrition. Molecular analyses with Fourier transform infrared spectroscopy (FT/IR) technique with attenuated total reflectance (ATR) and chemometrics enable to detect structural features on a molecular basis. The objectives of this study were to: (1) determine carbohydrate conformation spectral features in original carinata meal, co-products from bio-fuel/bio-oil processing; and (2) investigate differences in carbohydrate molecular composition and functional group spectral intensities after in situ ruminal fermentation at 0, 12, 24 and 48 h compared to canola meal as a reference. The molecular spectroscopic parameters of carbohydrate profiles detected were structural carbohydrates (STCHO, mainly associated with hemi-cellulosic and cellulosic compounds; region and baseline ca. 1483-1184 cm(-1)), cellulosic compounds (CELC, region and baseline ca. 1304-1184 cm(-1)), total carbohydrates (CHO, region and baseline ca. 1193-889cm(-1)) as well as the spectral ratios calculated based on respective spectral intensity data. The results showed that the spectral profiles of carinata meal were significantly different from that of canola meal in CHO 2nd peak area (center at ca. 1091 cm(-1), region: 1102-1083 cm(-1)) and functional group peak intensity ratios such as STCHO 1st peak (ca. 1415 cm(-1)) to 2nd peak (ca. 1374 cm(-1)) height ratio, CHO 1st peak (ca. 1149 cm(-1)) to 3rd peak (ca. 1032 cm(-1)) height ratio, CELC to total CHO area ratio and STCHO to CELC area ratio, indicating that carinata meal may not in full accord with canola meal in carbohydrate utilization and availability in ruminants. Carbohydrate conformation and spectral features were changed by significant interaction of meal type and incubation time and almost all the spectral parameters were significantly decreased (P<0.05) during 48 h ruminal degradation in both carinata meal and canola meal. Although carinata meal differed from canola meal in some carbohydrate spectral parameters, multivariate results from agglomerative hierarchical cluster analysis and principal component analysis showed that both original and in situ residues of two meals were not fully distinguished from each other within carbohydrate spectral regions. It was concluded that carbohydrate structural conformation could be detected in carinata meal by using ATR-FT/IR techniques and further study is needed to explore more information on molecular spectral features of other functional group such as protein structure profile and their association with potential nutrient supply and availability of carinata meal in animals. Copyright © 2013 Elsevier B.V. All rights reserved.

Multiple Scattering Principal Component-based Radiative Transfer Model (PCRTM) from Far IR to UV-Vis

NASA Astrophysics Data System (ADS)

Liu, X.; Wu, W.; Yang, Q.

2017-12-01

Modern satellite hyperspectral satellite remote sensors such as AIRS, CrIS, IASI, CLARREO all require accurate and fast radiative transfer models that can deal with multiple scattering of clouds and aerosols to explore the information contents. However, performing full radiative transfer calculations using multiple stream methods such as discrete ordinate (DISORT), doubling and adding (AD), successive order of scattering order of scattering (SOS) are very time consuming. We have developed a principal component-based radiative transfer model (PCRTM) to reduce the computational burden by orders of magnitudes while maintain high accuracy. By exploring spectral correlations, the PCRTM reduce the number of radiative transfer calculations in frequency domain. It further uses a hybrid stream method to decrease the number of calls to the computational expensive multiple scattering calculations with high stream numbers. Other fast parameterizations have been used in the infrared spectral region reduce the computational time to milliseconds for an AIRS forward simulation (2378 spectral channels). The PCRTM has been development to cover spectral range from far IR to UV-Vis. The PCRTM model have been be used for satellite data inversions, proxy data generation, inter-satellite calibrations, spectral fingerprinting, and climate OSSE. We will show examples of applying the PCRTM to single field of view cloudy retrievals of atmospheric temperature, moisture, traces gases, clouds, and surface parameters. We will also show how the PCRTM are used for the NASA CLARREO project.

Spectral element simulation of precession driven flows in the outer cores of spheroidal planets

NASA Astrophysics Data System (ADS)

Vormann, Jan; Hansen, Ulrich

2015-04-01

A common feature of the planets in the solar system is the precession of the rotation axes, driven by the gravitational influence of another body (e.g. the Earth's moon). In a precessing body, the rotation axis itself is rotating around another axis, describing a cone during one precession period. Similar to the coriolis and centrifugal force appearing from the transformation to a rotating system, the addition of precession adds another term to the Navier-Stokes equation, the so called Poincaré force. The main geophysical motivation in studying precession driven flows comes from their ability to act as magnetohydrodynamic dynamos in planets and moons. Precession may either act as the only driving force or operate together with other forces such as thermochemical convection. One of the challenges in direct numerical simulations of such flows lies in the spheroidal shape of the fluid volume, which should not be neglected since it contributes an additional forcing trough pressure torques. Codes developed for the simulation of flows in spheres mostly use efficient global spectral algorithms that converge fast, but lack geometric flexibility, while local methods are usable in more complex shapes, but often lack high accuracy. We therefore adapted the spectral element code Nek5000, developed at Argonne National Laboratory, to the problem. The spectral element method is capable of solving for the flow in arbitrary geometries while still offering spectral convergence. We present first results for the simulation of a purely hydrodynamic, precession-driven flow in a spheroid with no-slip boundaries and an inner core. The driving by the Poincaré force is in a range where theoretical work predicts multiple solutions for a laminar flow. Our simulations indicate a transition to turbulent flows for Ekman numbers of 10-6 and lower.

METALLICITY AND TEMPERATURE INDICATORS IN M DWARF K-BAND SPECTRA: TESTING NEW AND UPDATED CALIBRATIONS WITH OBSERVATIONS OF 133 SOLAR NEIGHBORHOOD M DWARFS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rojas-Ayala, Barbara; Covey, Kevin R.; Lloyd, James P.

2012-04-01

We present K-band spectra for 133 nearby (d < 33 ps) M dwarfs, including 18 M dwarfs with reliable metallicity estimates (as inferred from an FGK type companion), 11 M dwarf planet hosts, more than 2/3 of the M dwarfs in the northern 8 pc sample, and several M dwarfs from the LSPM catalog. From these spectra, we measure equivalent widths of the Ca and Na lines, and a spectral index quantifying the absorption due to H{sub 2}O opacity (the H{sub 2}O-K2 index). Using empirical spectral type standards and synthetic models, we calibrate the H{sub 2}O-K2 index as an indicatormore » of an M dwarf's spectral type and effective temperature. We also present a revised relationship that estimates the [Fe/H] and [M/H] metallicities of M dwarfs from their Na I, Ca I, and H{sub 2}O-K2 measurements. Comparisons to model atmosphere provide a qualitative validation of our approach, but also reveal an overall offset between the atomic line strengths predicted by models as compared to actual observations. Our metallicity estimates also reproduce expected correlations with Galactic space motions and H{alpha} emission line strengths, and return statistically identical metallicities for M dwarfs within a common multiple system. Finally, we find systematic residuals between our H{sub 2}O-based spectral types and those derived from optical spectral features with previously known sensitivity to stellar metallicity, such as TiO, and identify the CaH1 index as a promising optical index for diagnosing the metallicities of near-solar M dwarfs.« less

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California.

PubMed

Sousa, Daniel; Small, Christopher

2018-02-14

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area - despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California

PubMed Central

Small, Christopher

2018-01-01

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system. PMID:29443900

The Berkeley SuperNova Ia Program (BSNIP): Dataset and Initial Analysis

NASA Astrophysics Data System (ADS)

Silverman, Jeffrey; Ganeshalingam, M.; Kong, J.; Li, W.; Filippenko, A.

2012-01-01

I will present spectroscopic data from the Berkeley SuperNova Ia Program (BSNIP), their initial analysis, and the results of attempts to use spectral information to improve cosmological distance determinations to Type Ia supernova (SNe Ia). The dataset consists of 1298 low-redshift (z< 0.2) optical spectra of 582 SNe Ia observed from 1989 through the end of 2008. Many of the SNe have well-calibrated light curves with measured distance moduli as well as spectra that have been corrected for host-galaxy contamination. I will also describe the spectral classification scheme employed (using the SuperNova Identification code, SNID; Blondin & Tonry 2007) which utilizes a newly constructed set of SNID spectral templates. The sheer size of the BSNIP dataset and the consistency of the observation and reduction methods make this sample unique among all other published SN Ia datasets. I will also discuss measurements of the spectral features of about one-third of the spectra which were obtained within 20 days of maximum light. I will briefly describe the adopted method of automated, robust spectral-feature definition and measurement which expands upon similar previous studies. Comparisons of these measurements of SN Ia spectral features to photometric observables will be presented with an eye toward using spectral information to calculate more accurate cosmological distances. Finally, I will comment on related projects which also utilize the BSNIP dataset that are planned for the near future. This research was supported by NSF grant AST-0908886 and the TABASGO Foundation. I am grateful to Marc J. Staley for a Graduate Fellowship.

Fourier-transform-infrared-spectroscopy based spectral-biomarker selection towards optimum diagnostic differentiation of oral leukoplakia and cancer.

PubMed

Banerjee, Satarupa; Pal, Mousumi; Chakrabarty, Jitamanyu; Petibois, Cyril; Paul, Ranjan Rashmi; Giri, Amita; Chatterjee, Jyotirmoy

2015-10-01

In search of specific label-free biomarkers for differentiation of two oral lesions, namely oral leukoplakia (OLK) and oral squamous-cell carcinoma (OSCC), Fourier-transform infrared (FTIR) spectroscopy was performed on paraffin-embedded tissue sections from 47 human subjects (eight normal (NOM), 16 OLK, and 23 OSCC). Difference between mean spectra (DBMS), Mann-Whitney's U test, and forward feature selection (FFS) techniques were used for optimising spectral-marker selection. Classification of diseases was performed with linear and quadratic support vector machine (SVM) at 10-fold cross-validation, using different combinations of spectral features. It was observed that six features obtained through FFS enabled differentiation of NOM and OSCC tissue (1782, 1713, 1665, 1545, 1409, and 1161 cm(-1)) and were most significant, able to classify OLK and OSCC with 81.3 % sensitivity, 95.7 % specificity, and 89.7 % overall accuracy. The 43 spectral markers extracted through Mann-Whitney's U Test were the least significant when quadratic SVM was used. Considering the high sensitivity and specificity of the FFS technique, extracting only six spectral biomarkers was thus most useful for diagnosis of OLK and OSCC, and to overcome inter and intra-observer variability experienced in diagnostic best-practice histopathological procedure. By considering the biochemical assignment of these six spectral signatures, this work also revealed altered glycogen and keratin content in histological sections which could able to discriminate OLK and OSCC. The method was validated through spectral selection by the DBMS technique. Thus this method has potential for diagnostic cost minimisation for oral lesions by label-free biomarker identification.

Neural network modeling of a dolphin's sonar discrimination capabilities.

PubMed

Au, W W; Andersen, L N; Rasmussen, A R; Roitblat, H L; Nachtigall, P E

1995-07-01

The capability of an echolocating dolphin to discriminate differences in the wall thickness of cylinders was previously modeled by a counterpropagation neural network using only spectral information from the echoes. In this study, both time and frequency information were used to model the dolphin discrimination capabilities. Echoes from the same cylinders were digitized using a broadband simulated dolphin sonar signal with the transducer mounted on the dolphin's pen. The echoes were filtered by a bank of continuous constant-Q digital filters and the energy from each filter was computed in time increments of 1/bandwidth. Echo features of the standard and each comparison target were analyzed in pairs by a counterpropagation neural network, a backpropagation neural network, and a model using Euclidean distance measures. The backpropagation network performed better than both the counterpropagation network, and the Euclidean model, using either spectral-only features or combined temporal and spectral features. All models performed better using features containing both temporal and spectral information. The backpropagation network was able to perform better than the dolphins for noise-free echoes with Q values as low as 2 and 3. For a Q of 2, only temporal information was available. However, with noisy data, the network required a Q of 8 in order to perform as well as the dolphin.

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Spectral decompositions of multiple time series: a Bayesian non-parametric approach.

PubMed

Macaro, Christian; Prado, Raquel

2014-01-01

We consider spectral decompositions of multiple time series that arise in studies where the interest lies in assessing the influence of two or more factors. We write the spectral density of each time series as a sum of the spectral densities associated to the different levels of the factors. We then use Whittle's approximation to the likelihood function and follow a Bayesian non-parametric approach to obtain posterior inference on the spectral densities based on Bernstein-Dirichlet prior distributions. The prior is strategically important as it carries identifiability conditions for the models and allows us to quantify our degree of confidence in such conditions. A Markov chain Monte Carlo (MCMC) algorithm for posterior inference within this class of frequency-domain models is presented.We illustrate the approach by analyzing simulated and real data via spectral one-way and two-way models. In particular, we present an analysis of functional magnetic resonance imaging (fMRI) brain responses measured in individuals who participated in a designed experiment to study pain perception in humans.

The discovery of a new infrared emission feature at 1905 wavenumbers (5.25 microns) in the spectrum of BD + 30 deg 3639 and its relation to the polycyclic aromatic hydrocarbon model

NASA Technical Reports Server (NTRS)

Allamandola, L. J.; Bregman, J. D.; Sandford, S. A.; Tielens, A. G. G. M.; Witteborn, F. C.

1989-01-01

A new IR emission feature at 1905/cm (5.25 microns) has been discovered in the spectrum of BD + 30 deg 3639. This feature joins the family of well-known IR emission features at 3040, 2940, 1750, 1610, '1310', 1160, and 890/cm. The origin of this new feature is discussed and it is assigned to an overtone or combination band involving C-H bending modes of polycyclic aromatic hydrocarbons (PAHs). Laboratory work suggests that spectral studies of the 2000-1650/cm region may be very useful in elucidating the molecular structure of interstellar PAHs. The new feature, in conjunction with other recently discovered spectral structures, suggests that the narrow IR emission features originate in PAH molecules rather than large carbon grains.

Feature Selection for Ridge Regression with Provable Guarantees.

PubMed

Paul, Saurabh; Drineas, Petros

2016-04-01

We introduce single-set spectral sparsification as a deterministic sampling-based feature selection technique for regularized least-squares classification, which is the classification analog to ridge regression. The method is unsupervised and gives worst-case guarantees of the generalization power of the classification function after feature selection with respect to the classification function obtained using all features. We also introduce leverage-score sampling as an unsupervised randomized feature selection method for ridge regression. We provide risk bounds for both single-set spectral sparsification and leverage-score sampling on ridge regression in the fixed design setting and show that the risk in the sampled space is comparable to the risk in the full-feature space. We perform experiments on synthetic and real-world data sets; a subset of TechTC-300 data sets, to support our theory. Experimental results indicate that the proposed methods perform better than the existing feature selection methods.

Changes in the Spectral Features of Zinc Phthalocyanine Induced by Nitrogen Dioxide Gas in Solution and in Solid Polymer Nanofiber Media.

PubMed

Zugle, Ruphino; Tetteh, Samuel

2017-03-01

The changes in the spectral features of zinc phthalocyanine in the visible domain as a result of its interaction with nitrogen dioxide gas were assessed in this work. This was done both in solution and when the phthalocyanine was incorporated into a solid polystyrene polymer nanofiber matrix. The spectral changes were found to be spontaneous and marked in both cases suggesting a rapid response criterion for the detection of the gas. In particular, the functionalised nano-fabric material could serve as a practical fire alarm system as it rapidly detects the nitrogen dioxide gas generated during burning.

Mid-infrared (5.0-7.0 microns) imaging spectroscopy of the moon from the KAO

NASA Technical Reports Server (NTRS)

Bell, James F., III; Bregman, Jesse D.; Rank, David M.; Temi, Pasquale; Roush, Ted L.; Hawke, B. Ray; Lucey, Paul G.; Pollack, James B.

1995-01-01

A series of 71 mid-infrared images of a small region of the Moon were obtained from the KAO in October, 1993. These images have been assembled into a 5.0 to 7.0 micron image cube that has been calibrated relative to the average spectrum of this region of the Moon at these wavelengths. The data show that clear, detectable spectral differences exist on the Moon in the mid-IR. Some of the spectral differences are correlated with morphologic features such as craters. Specific spectral features near 5.6 and 6.7 microns may be related to the presence of plagioclase or pyroxene.

Adaptation to spectrally-rotated speech.

PubMed

Green, Tim; Rosen, Stuart; Faulkner, Andrew; Paterson, Ruth

2013-08-01

Much recent interest surrounds listeners' abilities to adapt to various transformations that distort speech. An extreme example is spectral rotation, in which the spectrum of low-pass filtered speech is inverted around a center frequency (2 kHz here). Spectral shape and its dynamics are completely altered, rendering speech virtually unintelligible initially. However, intonation, rhythm, and contrasts in periodicity and aperiodicity are largely unaffected. Four normal hearing adults underwent 6 h of training with spectrally-rotated speech using Continuous Discourse Tracking. They and an untrained control group completed pre- and post-training speech perception tests, for which talkers differed from the training talker. Significantly improved recognition of spectrally-rotated sentences was observed for trained, but not untrained, participants. However, there were no significant improvements in the identification of medial vowels in /bVd/ syllables or intervocalic consonants. Additional tests were performed with speech materials manipulated so as to isolate the contribution of various speech features. These showed that preserving intonational contrasts did not contribute to the comprehension of spectrally-rotated speech after training, and suggested that improvements involved adaptation to altered spectral shape and dynamics, rather than just learning to focus on speech features relatively unaffected by the transformation.

Using spectral information in forensic imaging.

PubMed

Miskelly, Gordon M; Wagner, John H

2005-12-20

Improved detection of forensic evidence by combining narrow band photographic images taken at a range of wavelengths is dependent on the substance of interest having a significantly different spectrum from the underlying substrate. While some natural substances such as blood have distinctive spectral features which are readily distinguished from common colorants, this is not true for visualization agents commonly used in forensic science. We now show that it is possible to select reagents with narrow spectral features that lead to increased visibility using digital cameras and computer image enhancement programs even if their coloration is much less intense to the unaided eye than traditional reagents. The concept is illustrated by visualising latent fingermarks on paper with the zinc complex of Ruhemann's Purple, cyanoacrylate-fumed fingerprints with Eu(tta)(3)(phen), and soil prints with 2,6-bis(benzimidazol-2-yl)-4-[4'-(dimethylamino)phenyl]pyridine [BBIDMAPP]. In each case background correction is performed at one or two wavelengths bracketing the narrow absorption or emission band of these compounds. However, compounds with sharp spectral features would also lead to improved detection using more advanced algorithms such as principal component analysis.

Multitaper scan-free spectrum estimation using a rotational shear interferometer.

PubMed

Lepage, Kyle; Thomson, David J; Kraut, Shawn; Brady, David J

2006-05-01

Multitaper methods for a scan-free spectrum estimation that uses a rotational shear interferometer are investigated. Before source spectra can be estimated the sources must be detected. A source detection algorithm based upon the multitaper F-test is proposed. The algorithm is simulated, with additive, white Gaussian detector noise. A source with a signal-to-noise ratio (SNR) of 0.71 is detected 2.9 degrees from a source with a SNR of 70.1, with a significance level of 10(-4), approximately 4 orders of magnitude more significant than the source detection obtained with a standard detection algorithm. Interpolation and the use of prewhitening filters are investigated in the context of rotational shear interferometer (RSI) source spectra estimation. Finally, a multitaper spectrum estimator is proposed, simulated, and compared with untapered estimates. The multitaper estimate is found via simulation to distinguish a spectral feature with a SNR of 1.6 near a large spectral feature. The SNR of 1.6 spectral feature is not distinguished by the untapered spectrum estimate. The findings are consistent with the strong capability of the multitaper estimate to reduce out-of-band spectral leakage.

Multitaper scan-free spectrum estimation using a rotational shear interferometer

NASA Astrophysics Data System (ADS)

Lepage, Kyle; Thomson, David J.; Kraut, Shawn; Brady, David J.

2006-05-01

Multitaper methods for a scan-free spectrum estimation that uses a rotational shear interferometer are investigated. Before source spectra can be estimated the sources must be detected. A source detection algorithm based upon the multitaper F-test is proposed. The algorithm is simulated, with additive, white Gaussian detector noise. A source with a signal-to-noise ratio (SNR) of 0.71 is detected 2.9° from a source with a SNR of 70.1, with a significance level of 10-4, ˜4 orders of magnitude more significant than the source detection obtained with a standard detection algorithm. Interpolation and the use of prewhitening filters are investigated in the context of rotational shear interferometer (RSI) source spectra estimation. Finally, a multitaper spectrum estimator is proposed, simulated, and compared with untapered estimates. The multitaper estimate is found via simulation to distinguish a spectral feature with a SNR of 1.6 near a large spectral feature. The SNR of 1.6 spectral feature is not distinguished by the untapered spectrum estimate. The findings are consistent with the strong capability of the multitaper estimate to reduce out-of-band spectral leakage.

Hyperspectral Imaging Sensors and the Marine Coastal Zone

NASA Technical Reports Server (NTRS)

Richardson, Laurie L.

2000-01-01

Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

NASA Astrophysics Data System (ADS)

Garbanzo-Salas, Marcial; Hocking, Wayne. K.

2015-09-01

In recent years, adaptive (data dependent) methods have been introduced into many areas where Fourier spectral analysis has traditionally been used. Although the data-dependent methods are often advanced as being superior to Fourier methods, they do require some finesse in choosing the order of the relevant filters. In performing comparisons, we have found some concerns about the mappings, particularly when related to cases involving many spectral lines or even continuous spectral signals. Using numerical simulations, several comparisons between Fourier transform procedures and minimum variance method (MVM) have been performed. For multiple frequency signals, the MVM resolves most of the frequency content only for filters that have more degrees of freedom than the number of distinct spectral lines in the signal. In the case of Gaussian spectral approximation, MVM will always underestimate the width, and can misappropriate the location of spectral line in some circumstances. Large filters can be used to improve results with multiple frequency signals, but are computationally inefficient. Significant biases can occur when using MVM to study spectral information or echo power from the atmosphere. Artifacts and artificial narrowing of turbulent layers is one such impact.

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

DTIC Science & Technology

2007-12-20

spectral bands are always facing the possibility of missing important spectral features of special cases, such as some coral reefs and/or seagrass ...Res. 1998, 103(C 10), 21,601-621,609. 16. Kirk, J. T. 0. 1994 Light & Photosynthesis in Aquatic Ecosystems, University Press, Cambridge. 17. Lee, Z

Onboard spectral imager data processor

NASA Astrophysics Data System (ADS)

Otten, Leonard J.; Meigs, Andrew D.; Franklin, Abraham J.; Sears, Robert D.; Robison, Mark W.; Rafert, J. Bruce; Fronterhouse, Donald C.; Grotbeck, Ronald L.

1999-10-01

Previous papers have described the concept behind the MightySat II.1 program, the satellite's Fourier Transform imaging spectrometer's optical design, the design for the spectral imaging payload, and its initial qualification testing. This paper discusses the on board data processing designed to reduce the amount of downloaded data by an order of magnitude and provide a demonstration of a smart spaceborne spectral imaging sensor. Two custom components, a spectral imager interface 6U VME card that moves data at over 30 MByte/sec, and four TI C-40 processors mounted to a second 6U VME and daughter card, are used to adapt the sensor to the spacecraft and provide the necessary high speed processing. A system architecture that offers both on board real time image processing and high-speed post data collection analysis of the spectral data has been developed. In addition to the on board processing of the raw data into a usable spectral data volume, one feature extraction technique has been incorporated. This algorithm operates on the basic interferometric data. The algorithm is integrated within the data compression process to search for uploadable feature descriptions.

FAINT EXTENDED OH EMISSION FROM THE LOCAL INTERSTELLAR MEDIUM IN THE DIRECTION l Almost-Equal-To 108 Degree-Sign , b Almost-Equal-To 5 Degree-Sign

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allen, Ronald J.; Rodriguez, Monica Ivette; Black, John H.

We have mapped faint 1667 OH line emission (T{sub A} Almost-Equal-To 20-40 mK in our Almost-Equal-To 30' beam) along many lines of sight in the Galaxy covering an area of Almost-Equal-To 4 Degree-Sign Multiplication-Sign 4 Degree-Sign in the general direction of l Almost-Equal-To 108 Degree-Sign , b Almost-Equal-To 5 Degree-Sign . The OH emission is widespread, similar in extent to the local H I (r {approx}< 2 kpc) both in space and in velocity. The OH profile amplitudes show a good general correlation with those of H I in spectral channels of Almost-Equal-To 1 km s{sup -1}; this relation ismore » described by T{sub A} (OH) Almost-Equal-To 1.50 Multiplication-Sign 10{sup -4} T{sub B} (H I) for values of T{sub B} (H I) {approx}< 60-70 K. Beyond this the H I line appears to 'saturate', and few values are recorded above Almost-Equal-To 90 K. However, the OH brightness continues to rise, by a further factor Almost-Equal-To 3. The OH velocity profiles show multiple features with widths typically 2-3 km s{sup -1}, but less than 10% of these features are associated with CO(1-0) emission in existing surveys of the area smoothed to comparable resolution.« less

Spectral Unmixing With Multiple Dictionaries

NASA Astrophysics Data System (ADS)

Cohen, Jeremy E.; Gillis, Nicolas

2018-02-01

Spectral unmixing aims at recovering the spectral signatures of materials, called endmembers, mixed in a hyperspectral or multispectral image, along with their abundances. A typical assumption is that the image contains one pure pixel per endmember, in which case spectral unmixing reduces to identifying these pixels. Many fully automated methods have been proposed in recent years, but little work has been done to allow users to select areas where pure pixels are present manually or using a segmentation algorithm. Additionally, in a non-blind approach, several spectral libraries may be available rather than a single one, with a fixed number (or an upper or lower bound) of endmembers to chose from each. In this paper, we propose a multiple-dictionary constrained low-rank matrix approximation model that address these two problems. We propose an algorithm to compute this model, dubbed M2PALS, and its performance is discussed on both synthetic and real hyperspectral images.

Spectrum recovery method based on sparse representation for segmented multi-Gaussian model

NASA Astrophysics Data System (ADS)

Teng, Yidan; Zhang, Ye; Ti, Chunli; Su, Nan

2016-09-01

Hyperspectral images can realize crackajack features discriminability for supplying diagnostic characteristics with high spectral resolution. However, various degradations may generate negative influence on the spectral information, including water absorption, bands-continuous noise. On the other hand, the huge data volume and strong redundancy among spectrums produced intense demand on compressing HSIs in spectral dimension, which also leads to the loss of spectral information. The reconstruction of spectral diagnostic characteristics has irreplaceable significance for the subsequent application of HSIs. This paper introduces a spectrum restoration method for HSIs making use of segmented multi-Gaussian model (SMGM) and sparse representation. A SMGM is established to indicating the unsymmetrical spectral absorption and reflection characteristics, meanwhile, its rationality and sparse property are discussed. With the application of compressed sensing (CS) theory, we implement sparse representation to the SMGM. Then, the degraded and compressed HSIs can be reconstructed utilizing the uninjured or key bands. Finally, we take low rank matrix recovery (LRMR) algorithm for post processing to restore the spatial details. The proposed method was tested on the spectral data captured on the ground with artificial water absorption condition and an AVIRIS-HSI data set. The experimental results in terms of qualitative and quantitative assessments demonstrate that the effectiveness on recovering the spectral information from both degradations and loss compression. The spectral diagnostic characteristics and the spatial geometry feature are well preserved.

A Review on Spectral Amplitude Coding Optical Code Division Multiple Access

NASA Astrophysics Data System (ADS)

Kaur, Navpreet; Goyal, Rakesh; Rani, Monika

2017-06-01

This manuscript deals with analysis of Spectral Amplitude Coding Optical Code Division Multiple Access (SACOCDMA) system. The major noise source in optical CDMA is co-channel interference from other users known as multiple access interference (MAI). The system performance in terms of bit error rate (BER) degrades as a result of increased MAI. It is perceived that number of users and type of codes used for optical system directly decide the performance of system. MAI can be restricted by efficient designing of optical codes and implementing them with unique architecture to accommodate more number of users. Hence, it is a necessity to design a technique like spectral direct detection (SDD) technique with modified double weight code, which can provide better cardinality and good correlation property.

Organic Haze as a Biosignature in Anoxic Earth-Like Atmospheres

NASA Technical Reports Server (NTRS)

Arney, Giada; Domagal-Goldman, Shawn D.; Meadows, Victoria S.

2017-01-01

Early Earth may have hosted a biologically mediated global organic haze during the Archean eon (3.8-2.5 billion years ago). This haze would have significantly impacted multiple aspects of our planet, including its potential for habitability and its spectral appearance. Here, we model worlds with Archean-like levels of carbon dioxide orbiting the ancient Sun and anM4Vdwarf (GJ 876) and show that organic haze formation requires methane fluxes consistent with estimated Earth-like biological production rates. On planets with high fluxes of biogenic organic sulfur gases (CS2, OCS, CH3SH, and CH3SCH3), photochemistry involving these gases can drive haze formation at lower CH4/CO2 ratios than methane photochemistry alone. For a planet orbiting the Sun, at 30x the modern organic sulfur gas flux, haze forms at a CH4/CO2 ratio 20% lower than at 1x the modern organic sulfur flux. For a planet orbiting the M4V star, the impact of organic sulfur gases is more pronounced: at 1x the modern Earth organic sulfur flux, a substantial haze forms at CH4/CO2 approx. 0.2, but at 30x the organic sulfur flux, the CH4/CO2 ratio needed to form haze decreases by a full order of magnitude. Detection of haze at an anomalously low CH4/ CO2 ratio could suggest the influence of these biogenic sulfur gases and therefore imply biological activity on an exoplanet. When these organic sulfur gases are not readily detectable in the spectrum of an Earth-like exoplanet, the thick organic haze they can help produce creates a very strong absorption feature at UV-blue wavelengths detectable in reflected light at a spectral resolution as low as 10. In direct imaging, constraining CH4 and CO2 concentrations will require higher spectral resolution, and R > 170 is needed to accurately resolve the structure of the CO2 feature at 1.57 microns, likely the most accessible CO2 feature on an Archean-like exoplanet.

Organic Haze as a Biosignature in Anoxic Earth-like Atmospheres

PubMed Central

Domagal-Goldman, Shawn D.; Meadows, Victoria S.

2018-01-01

Abstract Early Earth may have hosted a biologically mediated global organic haze during the Archean eon (3.8–2.5 billion years ago). This haze would have significantly impacted multiple aspects of our planet, including its potential for habitability and its spectral appearance. Here, we model worlds with Archean-like levels of carbon dioxide orbiting the ancient Sun and an M4V dwarf (GJ 876) and show that organic haze formation requires methane fluxes consistent with estimated Earth-like biological production rates. On planets with high fluxes of biogenic organic sulfur gases (CS2, OCS, CH3SH, and CH3SCH3), photochemistry involving these gases can drive haze formation at lower CH4/CO2 ratios than methane photochemistry alone. For a planet orbiting the Sun, at 30× the modern organic sulfur gas flux, haze forms at a CH4/CO2 ratio 20% lower than at 1× the modern organic sulfur flux. For a planet orbiting the M4V star, the impact of organic sulfur gases is more pronounced: at 1× the modern Earth organic sulfur flux, a substantial haze forms at CH4/CO2 ∼ 0.2, but at 30× the organic sulfur flux, the CH4/CO2 ratio needed to form haze decreases by a full order of magnitude. Detection of haze at an anomalously low CH4/CO2 ratio could suggest the influence of these biogenic sulfur gases and therefore imply biological activity on an exoplanet. When these organic sulfur gases are not readily detectable in the spectrum of an Earth-like exoplanet, the thick organic haze they can help produce creates a very strong absorption feature at UV-blue wavelengths detectable in reflected light at a spectral resolution as low as 10. In direct imaging, constraining CH4 and CO2 concentrations will require higher spectral resolution, and R > 170 is needed to accurately resolve the structure of the CO2 feature at 1.57 μm, likely the most accessible CO2 feature on an Archean-like exoplanet. Key Words: Organic haze—Organic sulfur gases—Biosignatures—Archean Earth. Astrobiology 18, 311–329. PMID:29189040

Environmental Consequences of an Emerging Biosphere

NASA Technical Reports Server (NTRS)

DesMarais, David J.

2003-01-01

It seems feasible to detect biological signatures ("biosignatures") in other planetary systems using the tools of astronomy. There are at least two types of biosignatures; spectral and/or polarization features created by biological products, and electromagnetic signals created by technology. The latter example of a biosignature requires SETI-like searches. This presentation addresses only spectral signatures of biological products and properties of habitable planets. Spectral biosignatures are indeed promising targets for near-term exploration. They can arise from organic constituents (e.g., vegetation) and/or inorganic products (e.g., atmospheric O2). Features originating from a planet's surface are likely to be localized in specific regions, whereas gaseous biosignatures can become globally distributed by atmospheric circulation. Biosignatures should be most abundant within environments that are, or once were, habitable. We currently believe that habitable environments necessarily provide Liquid water and biochemically useful energy. However, we do not yet fully comprehend the diversity of features that might arise within these environments that are non-biological in origin, yet mimic biosignatures. For example, atmospheres reflect the events leading to their origins as well as a host of ongoing planetary processes that might include biological activity. We are persuaded that abundant atmospheric oxygen in an environment with abundant liquid water constitutes definitive evidence of life. However, our own early biosphere thrived for more than a billion years in the absence of abundant atmospheric oxygen. The production of other, more reduced, gaseous biomarkers of "young" and/or anaerobic biospheres has not been systematically studied. Biological gas production is strongly controlled by the structure and function of microbial ecosystems. Investigations of microbial ecosystems that are close analogs of ancient communities offer multiple benefits. Such studies can interpret the production of the most important biomarker gases, while simultaneously helping us to understand the formidable array of ecological processes that guided early biological evolution. Astrobiologists must recognize those aspects of biosignatures that truly reflect the most fundamental, and therefore universal, properties of life. We must learn how the environment can modify biosignatures, and how technology can enable an array of biosignatures to be detected remotely within realistic budgetary constraints

Organic Haze as a Biosignature in Anoxic Earth-like Atmospheres.

PubMed

Arney, Giada; Domagal-Goldman, Shawn D; Meadows, Victoria S

2018-03-01

Early Earth may have hosted a biologically mediated global organic haze during the Archean eon (3.8-2.5 billion years ago). This haze would have significantly impacted multiple aspects of our planet, including its potential for habitability and its spectral appearance. Here, we model worlds with Archean-like levels of carbon dioxide orbiting the ancient Sun and an M4V dwarf (GJ 876) and show that organic haze formation requires methane fluxes consistent with estimated Earth-like biological production rates. On planets with high fluxes of biogenic organic sulfur gases (CS 2 , OCS, CH 3 SH, and CH 3 SCH 3 ), photochemistry involving these gases can drive haze formation at lower CH 4 /CO 2 ratios than methane photochemistry alone. For a planet orbiting the Sun, at 30× the modern organic sulfur gas flux, haze forms at a CH 4 /CO 2 ratio 20% lower than at 1× the modern organic sulfur flux. For a planet orbiting the M4V star, the impact of organic sulfur gases is more pronounced: at 1× the modern Earth organic sulfur flux, a substantial haze forms at CH 4 /CO 2 ∼ 0.2, but at 30× the organic sulfur flux, the CH 4 /CO 2 ratio needed to form haze decreases by a full order of magnitude. Detection of haze at an anomalously low CH 4 /CO 2 ratio could suggest the influence of these biogenic sulfur gases and therefore imply biological activity on an exoplanet. When these organic sulfur gases are not readily detectable in the spectrum of an Earth-like exoplanet, the thick organic haze they can help produce creates a very strong absorption feature at UV-blue wavelengths detectable in reflected light at a spectral resolution as low as 10. In direct imaging, constraining CH 4 and CO 2 concentrations will require higher spectral resolution, and R > 170 is needed to accurately resolve the structure of the CO 2 feature at 1.57 μm, likely the most accessible CO 2 feature on an Archean-like exoplanet. Key Words: Organic haze-Organic sulfur gases-Biosignatures-Archean Earth. Astrobiology 18, 311-329.

Classification of tree species based on longwave hyperspectral data from leaves, a case study for a tropical dry forest

NASA Astrophysics Data System (ADS)

Harrison, D.; Rivard, B.; Sánchez-Azofeifa, A.

2018-04-01

Remote sensing of the environment has utilized the visible, near and short-wave infrared (IR) regions of the electromagnetic (EM) spectrum to characterize vegetation health, vigor and distribution. However, relatively little research has focused on the use of the longwave infrared (LWIR, 8.0-12.5 μm) region for studies of vegetation. In this study LWIR leaf reflectance spectra were collected in the wet seasons (May through December) of 2013 and 2014 from twenty-six tree species located in a high species diversity environment, a tropical dry forest in Costa Rica. A continuous wavelet transformation (CWT) was applied to all spectra to minimize noise and broad amplitude variations attributable to non-compositional effects. Species discrimination was then explored with Random Forest classification and accuracy improved was observed with preprocessing of reflectance spectra with continuous wavelet transformation. Species were found to share common spectral features that formed the basis for five spectral types that were corroborated with linear discriminate analysis. The source of most of the observed spectral features is attributed to cell wall or cuticle compounds (cellulose, cutin, matrix glycan, silica and oleanolic acid). Spectral types could be advantageous for the analysis of airborne hyperspectral data because cavity effects will lower the spectral contrast thus increasing the reliance of classification efforts on dominant spectral features. Spectral types specifically derived from leaf level data are expected to support the labeling of spectral classes derived from imagery. The results of this study and that of Ribeiro Da Luz (2006), Ribeiro Da Luz and Crowley (2007, 2010), Ullah et al. (2012) and Rock et al. (2016) have now illustrated success in tree species discrimination across a range of ecosystems using leaf-level spectral observations. With advances in LWIR sensors and concurrent improvements in their signal to noise, applications to large-scale species detection from airborne imagery appear feasible.

Estimating Water Ice Abundance from Short-Wave Infrared Spectra of Drill Cuttings at Cryogenic Temperatures

NASA Technical Reports Server (NTRS)

Roush, Ted L.; Colaprete, Anthony; Kleinhenz, Julie; Cook, Amanda

2017-01-01

NASA's Resource Prospector (RP) mission intends to visit a lunar polar region to characterize the volatile distribution. Part of the RP payload, the Near-infrared Volatile Spectrometer System (NIRVSS) is a spectrometer operating from 1600-3400 nm that provides sensitivity to water ice, and other volatiles. For multiple years, the NIRVSS system has been incorporated into on-going RP payload testing in a cryogenic vacuum facility at Glenn Research Center. Soil tubes of lunar simulants, prepared with known amounts of water, are placed in the vacuum chamber and cooled to cryogenic temperatures (soil temperatures of 110-170 K) and placed under low vacuum (a few x 10(exp -6) Torr). During these tests NIRVSS continuously measures spectra of soil cuttings emplaced onto the surface by a drill. Real time processing of NIRVSS spectra produces two spectral parameters associated with water ice absorption features near 2000 and 3000 nm that can be used to inform decision making activities such as delivery of the soil to a sealable container. Post-test collection and analyses of the soils permit characterization the water content as a function of depth. These water content profiles exhibit the characteristics of a vacuum desiccation zone to depths of about 40 cm. Subsequent to completion of the tests, NIRVSS spectra are processed to produce two spectral parameters associated with water ice absorption features near 2000 and 3000 nm. These features can be evaluated as a function of time, and correlated with drill depth, and other measurements, throughout the drilling activities. Until now no effort was attempted to quantitatively relate these parameters to water abundance. This is the focus of our efforts to be presented.

Estimating Water Ice Abundance from Short-wave Infrared Spectra of Drill Cuttings at Cryogenic Temperatures

NASA Astrophysics Data System (ADS)

Roush, T. L.; Colaprete, A.; Kleinhenz, J.; Cook, A.

2017-12-01

NASA's Resource Prospector (RP) mission intends to visit a lunar polar region to characterize the volatile distribution. Part of the RP payload, the Near-infrared Volatile Spectrometer System (NIRVSS) is a spectrometer operating from 1600-3400 nm that provides sensitivity to water ice, and other volatiles. For multiple years, the NIRVSS system has been incorporated into on-going RP payload testing in a cryogenic vacuum facility at Glenn Research Center. Soil tubes of lunar simulants, prepared with known amounts of water, are placed in the vacuum chamber and cooled to cryogenic temperatures (soil temperatures of 110-170° K) and placed under low vacuum (a few x 10-6 Torr). During these tests NIRVSS continuously measures spectra of soil cuttings emplaced onto the surface by a drill. Real time processing of NIRVSS spectra produces two spectral parameters associated with water ice absorption features near 2000 and 3000 nm that can be used to inform decision-making activities such as delivery of the soil to a sealable container. Post-test collection and analyses of the soils permit characterization the water content as a function of depth. These water content profiles exhibit the characteristics of a vacuum desiccation zone to depths of about 40 cm. Subsequent to completion of the tests, NIRVSS spectra are processed to produce two spectral parameters associated with water ice absorption features near 2000 and 3000 nm. These features can be evaluated as a function of time, and correlated with drill depth, and other measurements, throughout the drilling activities. Until now no effort was attempted to quantitatively relate these parameters to water abundance. This is the focus of our efforts to be presented.

Seismic wavefield propagation in 2D anisotropic media: Ray theory versus wave-equation simulation

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; Hu, Guang-yi; Zhang, Yan-teng; Li, Zhong-sheng

2014-05-01

Despite the ray theory that is based on the high frequency assumption of the elastic wave-equation, the ray theory and the wave-equation simulation methods should be mutually proof of each other and hence jointly developed, but in fact parallel independent progressively. For this reason, in this paper we try an alternative way to mutually verify and test the computational accuracy and the solution correctness of both the ray theory (the multistage irregular shortest-path method) and the wave-equation simulation method (both the staggered finite difference method and the pseudo-spectral method) in anisotropic VTI and TTI media. Through the analysis and comparison of wavefield snapshot, common source gather profile and synthetic seismogram, it is able not only to verify the accuracy and correctness of each of the methods at least for kinematic features, but also to thoroughly understand the kinematic and dynamic features of the wave propagation in anisotropic media. The results show that both the staggered finite difference method and the pseudo-spectral method are able to yield the same results even for complex anisotropic media (such as a fault model); the multistage irregular shortest-path method is capable of predicting similar kinematic features as the wave-equation simulation method does, which can be used to mutually test each other for methodology accuracy and solution correctness. In addition, with the aid of the ray tracing results, it is easy to identify the multi-phases (or multiples) in the wavefield snapshot, common source point gather seismic section and synthetic seismogram predicted by the wave-equation simulation method, which is a key issue for later seismic application.

Red and near-infrared fluorophores inspired by chlorophylls: consideration of practical brightness in multicolor flow cytometry and biomedical sciences

NASA Astrophysics Data System (ADS)

Taniguchi, Masahiko; Hu, Gongfang; Liu, Rui; Du, Hai; Lindsey, Jonathan S.

2018-02-01

Demands in flow cytometry for increased multiplexing (for detection of multiple antigens) and brightness (for detection of rare entities) require new fluorophores (i.e., "colors") with spectrally distinct fluorescence outside the relatively congested visible spectral region. Flow cytometry fluorophores typically must function in aqueous solution upon bioconjugation and ideally should exhibit a host of photophysical features: (i) strong absorption, (ii) sizable Stokes shift, (iii) modest if not strong fluorescence, and (iv) narrow fluorescence band. Tandem dyes have long been pursued to achieve a large effective Stokes shift, increased brightness, and better control over the excitation and emission wavelengths. Here, the attractive photophysical features of chlorophylls and bacteriochlorophylls - Nature's chosen photoactive pigments for photosynthesis - are described with regards to use in flow cytometry. A chlorophyll (or bacteriochlorophyll) constitutes an intrinsic tandem dye given the red (or near-infrared) fluorescence upon excitation in the higher energy ultraviolet (UV) or visible absorption bands (due to rapid internal conversion to the lowest energy state). Synthetic (bacterio)chlorins are available with strong absorption (near-UV molar absorption coefficient ɛ(λexc) 105 M-1cm-1), modest fluorescence quantum yield (Φf = 0.05-0.30), and narrow fluorescence band (10-25 nm) tunable from 600-900 nm depending on synthetic design. The "relative practical brightness" is given by intrinsic brightness [ɛ(λexc) x Φf] times ηf, the fraction of the fluorescence band that is captured by an emission filter in a multicolor experiment. The spectroscopic features of (bacterio)chlorins are evaluated quantitatively to illustrate practical brightness for this novel class of fluorophores in a prospective 8-color panel.

Thermal Effects of Lunar Surface Roughness: Application for the 2008 LRO Diviner Lunar Radiometer Experiment

NASA Astrophysics Data System (ADS)

Greenhagen, B.; Paige, D. A.

2007-12-01

It is well known that surface roughness affects spectral slope in the infrared. For the first time, we applied a three-dimensional thermal model to a high resolution lunar topography map to study the effects of surface roughness on lunar thermal emission spectra. We applied a numerical instrument model of the upcoming Diviner Lunar Radiometer Experiment (DLRE) to simulate the expected instrument response to surface roughness variations. The Diviner Lunar Radiometer Experiment (DLRE) will launch in late 2008 onboard the Lunar Reconnaissance Orbiter (LRO). DLRE is a nine-channel radiometer designed to study the thermal and petrologic properties of the lunar surface. DLRE has two solar channels (0.3-3.0 μm high/low sensitivity), three mid-infrared petrology channels (7.55-8.05, 8.10-8.40 8.40-8.70 μm), and four thermal infrared channels (12.5-25, 25-50, 50-100, and 100-200 μm). The topographic data we used was selected from a USGS Hadley Rille DEM (from Apollo 15 Panoramic Camera data) with 10 m resolution (M. Rosiek; personal communication). To remove large scale topographic features, we applied a 200 x 200 pixel boxcar high-pass filter to a relatively flat portion of the DEM. This "flattened" surface roughness map served as the basis for much of this study. We also examined the unaltered topography. Surface temperatures were calculated using a three-dimensional ray tracing thermal model. We created temperature maps at numerous solar incidence angles with nadir viewing geometry. A DLRE instrument model, which includes filter spectral responses and detector fields of view, was applied to the high resolution temperature maps. We studied both the thermal and petrologic effects of surface roughness. For the thermal study, the output of the optics model is a filter specific temperature, scaled to a DLRE footprint of < 500 m. For the petrologic study, we examined the effect of the surface roughness induced spectral slope on the DLRE's ability to locate the Christiansen Feature, which is a good compositional indicator. With multiple thermal infrared channels over a wide spectral range, DLRE will be well suited to measure temperature variations due to surface roughness. Any necessary compensation (e.g. correction for spectral slope) to the mid-infrared petrology data will be performed.

Textural signatures for wetland vegetation

NASA Technical Reports Server (NTRS)

Whitman, R. I.; Marcellus, K. L.

1973-01-01

This investigation indicates that unique textural signatures do exist for specific wetland communities at certain times in the growing season. When photographs with the proper resolution are obtained, the textural features can identify the spectral features of the vegetation community seen with lower resolution mapping data. The development of a matrix of optimum textural signatures is the goal of this research. Seasonal variations of spectral and textural features are particularly important when performing a vegetations analysis of fresh water marshes. This matrix will aid in flight planning, since expected seasonal variations and resolution requirements can be established prior to a given flight mission.

Visible and Near-IR Reflectance Spectra of Smectite Acquired Under Dry Conditions for Interpretation of Martian Surface Mineralogy

NASA Technical Reports Server (NTRS)

Morris, Richard V.; Achilles, Cherie N; Archer, Paul D.; Graff, Trevor G.; Agresti, David G.; Ming, Douglas W; Golden, Dadi C.; Mertzman, Stanley A.

2011-01-01

Visible and near-IR (VNIR) spectra from the MEx OMEGA and the MRO CRISM hyper-spectral imaging instruments have spectral features associated with the H2O molecule and M OH functional groups (M = Mg, Fe, Al, and Si). Mineralogical assignments of martian spectral features are made on the basis of laboratory VNIR spectra, which were often acquired under ambient (humid) conditions. Smectites like nontronite, saponite, and montmorillionite have interlayer H2O that is exchangeable with their environment, and we have acquired smectite reflectance spectra under dry environmental conditions for interpretation of martian surface mineralogy. We also obtained chemical, Moessbauer (MB), powder X-ray diffraction (XRD), and thermogravimetric (TG) data to understand variations in spectral properties. VNIR spectra were recorded in humid lab air at 25-35C, in a dynamic dry N2 atmosphere (50-150 ppmv H2O) after exposing the smectite samples (5 nontronites, 3 montmorillionites, and 1 saponite) to that atmosphere for up to approximately l000 hr each at 25-35C, approximately 105C, and approximately 215C, and after re-exposure to humid lab air. Heating at 105C and 215C for approximately 1000 hr is taken as a surrogate for geologic time scales at lower temperatures. Upon exposure to dry N2, the position and intensity of spectral features associated with M-OH were relatively insensitive to the dry environment, and the spectral features associated with H2O (e.g., approximately 1.90 micrometers) decreased in intensity and are sometimes not detectable by the end of the 215C heating step. The position and intensity of H2O spectral features recovered upon re-exposure to lab air. XRD data show interlayer collapse for the nontronites and Namontmorillionites, with the interlayer remaining collapsed for the latter after re-exposure to lab air. The interlayer did not collapse for the saponite and Ca-montmorillionite. TG data show that the concentration of H2O derived from structural OH was invariant to the dry N2 treatment for saponite and the montmorillionites, but the nontronites had additional structural OH after treatment. Upon exposure to dry N2, the VNIR spectra also acquired a red slope with decreasing albedo between approximately 0.4 and approximately 2.0 micrometers. The magnitude of the effects covaries with exposure time to dry N2 and heating temperature. Upon re-exposure to lab air, the slope and albedo do not completely recover to pre-exposure values. MB data show that these effects do not result from partial reduction of ferric to ferrous iron, and TG data show they do not result from loss of structural OH. Possible explanations include formation of small clusters of (superparamagnetic) ferric oxide and reduced smectite crystallinity. The difference in spectral properties between spectra acquired in humid lab air and under dry conditions are consequential for interpretation of CRISM and OMEGA spectra. For example, nontronite by itself and not nontronite plus ferrihydrite can account for the red spectral slope in martian spectra where nontronite is indicated by the Fe-OH spectral features.

Automatic sub-pixel coastline extraction based on spectral mixture analysis using EO-1 Hyperion data

NASA Astrophysics Data System (ADS)

Hong, Zhonghua; Li, Xuesu; Han, Yanling; Zhang, Yun; Wang, Jing; Zhou, Ruyan; Hu, Kening

2018-06-01

Many megacities (such as Shanghai) are located in coastal areas, therefore, coastline monitoring is critical for urban security and urban development sustainability. A shoreline is defined as the intersection between coastal land and a water surface and features seawater edge movements as tides rise and fall. Remote sensing techniques have increasingly been used for coastline extraction; however, traditional hard classification methods are performed only at the pixel-level and extracting subpixel accuracy using soft classification methods is both challenging and time consuming due to the complex features in coastal regions. This paper presents an automatic sub-pixel coastline extraction method (ASPCE) from high-spectral satellite imaging that performs coastline extraction based on spectral mixture analysis and, thus, achieves higher accuracy. The ASPCE method consists of three main components: 1) A Water- Vegetation-Impervious-Soil (W-V-I-S) model is first presented to detect mixed W-V-I-S pixels and determine the endmember spectra in coastal regions; 2) The linear spectral mixture unmixing technique based on Fully Constrained Least Squares (FCLS) is applied to the mixed W-V-I-S pixels to estimate seawater abundance; and 3) The spatial attraction model is used to extract the coastline. We tested this new method using EO-1 images from three coastal regions in China: the South China Sea, the East China Sea, and the Bohai Sea. The results showed that the method is accurate and robust. Root mean square error (RMSE) was utilized to evaluate the accuracy by calculating the distance differences between the extracted coastline and the digitized coastline. The classifier's performance was compared with that of the Multiple Endmember Spectral Mixture Analysis (MESMA), Mixture Tuned Matched Filtering (MTMF), Sequential Maximum Angle Convex Cone (SMACC), Constrained Energy Minimization (CEM), and one classical Normalized Difference Water Index (NDWI). The results from the three test sites indicated that the proposed ASPCE method extracted coastlines more efficiently than did the compared methods, and its coastline extraction accuracy corresponded closely to the digitized coastline, with 0.39 pixels, 0.40 pixels, and 0.35 pixels in the three test regions, showing that the ASPCE method achieves an accuracy below 12.0 m (0.40 pixels). Moreover, in the quantitative accuracy assessment for the three test sites, the ASPCE method shows the best performance in coastline extraction, achieving a 0.35 pixel-level at the Bohai Sea, China test site. Therefore, the proposed ASPCE method can extract coastline more accurately than can the hard classification methods or other spectral unmixing methods.

Examination of the spectral features of vegetation in 1987 AVIRIS data

NASA Technical Reports Server (NTRS)

Elvidge, Christopher D.

1988-01-01

Equations for converting AVIRIS digital numbers to percent reflectance were developed using a set of three calibration targets. AVIRIS reflectance spectra from five plant communities exhibit distinct spectral differences.

Spectral features of solar plasma flows

NASA Astrophysics Data System (ADS)

Barkhatov, N. A.; Revunov, S. E.

2014-11-01

Research to the identification of plasma flows in the Solar wind by spectral characteristics of solar plasma flows in the range of magnetohydrodynamics is devoted. To do this, the wavelet skeleton pattern of Solar wind parameters recorded on Earth orbit by patrol spacecraft and then executed their neural network classification differentiated by bandwidths is carry out. This analysis of spectral features of Solar plasma flows in the form of magnetic clouds (MC), corotating interaction regions (CIR), shock waves (Shocks) and highspeed streams from coronal holes (HSS) was made. The proposed data processing and the original correlation-spectral method for processing information about the Solar wind flows for further classification as online monitoring of near space can be used. This approach will allow on early stages in the Solar wind flow detect geoeffective structure to predict global geomagnetic disturbances.

The design and application of a multi-band IR imager

NASA Astrophysics Data System (ADS)

Li, Lijuan

2018-02-01

Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection.

PubMed

Kumar Myakalwar, Ashwin; Spegazzini, Nicolas; Zhang, Chi; Kumar Anubham, Siva; Dasari, Ramachandra R; Barman, Ishan; Kumar Gundawar, Manoj

2015-08-19

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the 'curse of dimensionality' have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers -based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations.

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection

PubMed Central

Kumar Myakalwar, Ashwin; Spegazzini, Nicolas; Zhang, Chi; Kumar Anubham, Siva; Dasari, Ramachandra R.; Barman, Ishan; Kumar Gundawar, Manoj

2015-01-01

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the ‘curse of dimensionality’ have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers –based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations. PMID:26286630

Evaluation of wavelet spectral features in pathological detection and discrimination of yellow rust and powdery mildew in winter wheat with hyperspectral reflectance data

NASA Astrophysics Data System (ADS)

Shi, Yue; Huang, Wenjiang; Zhou, Xianfeng

2017-04-01

Hyperspectral absorption features are important indicators of characterizing plant biophysical variables for the automatic diagnosis of crop diseases. Continuous wavelet analysis has proven to be an advanced hyperspectral analysis technique for extracting absorption features; however, specific wavelet features (WFs) and their relationship with pathological characteristics induced by different infestations have rarely been summarized. The aim of this research is to determine the most sensitive WFs for identifying specific pathological lesions from yellow rust and powdery mildew in winter wheat, based on 314 hyperspectral samples measured in field experiments in China in 2002, 2003, 2005, and 2012. The resultant WFs could be used as proxies to capture the major spectral absorption features caused by infestation of yellow rust or powdery mildew. Multivariate regression analysis based on these WFs outperformed conventional spectral features in disease detection; meanwhile, a Fisher discrimination model exhibited considerable potential for generating separable clusters for each infestation. Optimal classification returned an overall accuracy of 91.9% with a Kappa of 0.89. This paper also emphasizes the WFs and their relationship with pathological characteristics in order to provide a foundation for the further application of this approach in monitoring winter wheat diseases at the regional scale.

Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

2018-01-01

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

Insight into resolution enhancement in generalized two-dimensional correlation spectroscopy.

PubMed

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K; Asher, Sanford A

2013-03-01

Generalized two-dimensional correlation spectroscopy (2D-COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D-COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) is not completely understood. In the work here, we studied the 2D-COS of simulated spectra in order to develop new insights into the dependence of 2D-COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We found that the features in the 2D-COS maps that are derived from overlapping bands were determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identified the conditions required to resolve overlapping bands. In particular, 2D-COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands.

Insight into Resolution Enhancement in Generalized Two-Dimensional Correlation Spectroscopy

PubMed Central

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K.; Asher, Sanford A.

2014-01-01

Generalized two-dimensional correlation spectroscopy (2D COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) are not completely understood. In the work here we studied the 2D COS of simulated spectra in order to develop new insights into the dependence of the 2D COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We find that the features in the 2D COS maps that derive from overlapping bands are determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identify the conditions required to resolve overlapping bands. In particular, 2D COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands. PMID:23452492

Spatially resolved bimodal spectroscopy for classification/evaluation of mouse skin inflammatory and pre-cancerous stages

NASA Astrophysics Data System (ADS)

Díaz-Ayil, Gilberto; Amouroux, Marine; Clanché, Fabien; Granjon, Yves; Blondel, Walter C. P. M.

2009-07-01

Spatially-resolved bimodal spectroscopy (multiple AutoFluorescence AF excitation and Diffuse Reflectance DR), was used in vivo to discriminate various healthy and precancerous skin stages in a pre-clinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A specific data preprocessing scheme was applied to intensity spectra (filtering, spectral correction and intensity normalization), and several sets of spectral characteristics were automatically extracted and selected based on their discrimination power, statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of Sensibility (Se) and Specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibres distances and of the numbers of principal components, such that: Se and Sp ~ 100% when discriminating CH vs. others; Sp ~ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ~ 74% and Se ~ 63% for AH vs. D.

Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Berglund, Judith

2000-01-01

The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

High-Energy Density science at the Linac Coherent Light Source

NASA Astrophysics Data System (ADS)

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-03-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. In recent experiments we have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on a scattering length comparable to the screening length. This technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.

High-Energy Density science at the Linac Coherent Light Source

DOE PAGES

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-04-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. Recently, our experiments have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on amore » scattering length comparable to the screening length. Moreover, this technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.« less

A Comparison of the Near-Infrared Spectral Features of Early-Type Galaxies in the Virgo and Coma Clusters

NASA Astrophysics Data System (ADS)

Houdashelt, M. L.

1992-05-01

Initial results are presented from an examination of near-infrared spectra (6800 - 9200 Angstroms) of 34 early-type galaxies - 17 in the Virgo cluster, 10 in the Coma cluster and seven field members. It has previously been speculated that E/S0 galaxies of similar luminosity in the Virgo and Coma clusters have different red stellar populations. To explore this possibility, pseudo-equivalent widths of a number of near-IR spectral features have been measured. The important features studied include the TiO bands near 7100, 7890, 8197, 8500 and 8950 Angstroms, which are mainly produced by the late-type stars whose flux contributes only about 10-20\\ the near-IR. The strengths of the Ca triplet (8498, 8542, 8662 Angstroms) and Na I doublet (8183, 8195 Angstroms) are also measured, since these features are affected by the relative contribution of dwarf stars to the red light. Although the main focus of this work is the search for spectral differences among the Coma, Virgo and field E/S0 populations, each subgroup of galaxies (and the sample as a whole) are also examined for correlations among the feature strengths, galaxy color and luminosity.

Computer modeling of bidirectional spectra: the role of geometry of illumination/observation

NASA Astrophysics Data System (ADS)

Grynko, Ye.; Shkuratov, Yu.; Mall, U.

Reflectance spectroscopy is widely used in the remote sensing of the Moon. Ground based and space spectrophotometric observations provide information about physical properties and chemical composition of lunar regolith. The main spectral features such as spectral slope and parameters of the absorption bands are different for different minerals and depend on the surface roughness, particle size, degrees of maturity and cristallinity, etc. In order to interpret reflectance measurements a model describing the light interaction with a regolith-like surface is needed. However, the problem of light scattering in dense particulate media consisting of irregular particles larger than the wavelength of light (which is the case for lunar regolith) has not yet been solved and only approximate models exist. Spectrophotometric properties of such surfaces can be analyzed in the geometric optics approach with one-dimensional (1-D) light scattering models (e.g., [1]). Although the 1-D models are successfully applied to interprete planetary regolith spectra they do not give an answer how spectral features depend on the geometrical illumination/observation condition of the surface. Laboratory measurements prove that the changing lighting conditions play a significant role in the formation of the above mentioned spectral features [2, 3]. In the presented work we use computer modeling to simulate light reflection from a regolith-like surface. Our computer experiment includes two stages: The simulation of the medium and ray tracing [4, 5]. Particles with random irregular shape are randomly distributed in a cyclically closed model volume which forms a semi-infinite medium (surface). Their surface is described by flat facets.The applied technique uses a Monte Carlo ray tracing method with parallel rays falling under a given angle relative to the average surface normal. The interaction of a ray with a particle surface facet is determined by Fresnel formulas and Snell's law. The model delivers the absolute surface reflectance as function of wavelength for a given geometrical illumination/observation condition In this paper we study the dependence of the reflectance spectra on the phase angle. The angle of incidence is constant and equals to 70°. The phase angle changes from 0° to 160°. For the substance which the particles are made of we chose average value 1 for the complex refractive index corresponding to lunar mare and highlands. Our calculations reveal a strong dependence of the spectral slopes on the phase angle. This confirms the previous general conclusion given in [2] that the larger the phase angle is the redder is the spectrum. A decomposition of the reflected flux into different scattering components shows that this is caused by the indicatrix of single scattering. Multiple scattering has almost no influence on spectral slope. The shape of the absorption bands also varies with phase angle but this dependence is not regular. The 1 µm feature is more pronounced at small and moderate phase angles and becomes wide and less visible at very large phase angles. References. [1] Yu. Shkuratov et al., Icarus, 137, 235-246 (1999). [2] C. M. Pieters et al., LPSC XXII, Abstract #1069 (1991). [3] A. Cord et al., Icarus, 165, 414-427 (2003). [4] Ye. Grynko and Yu. Shkuratov, J. Quant. Spectrosc. Rad. Trans. 78, 319- 340 (2003). [5] Yu. Shkuratov and Ye. Grynko, Icarus, 173, 16-28 (2006). 2

Spectrum Analyzers Incorporating Tunable WGM Resonators

NASA Technical Reports Server (NTRS)

Savchenkov, Anatoliy; Matsko, Andrey; Strekalov, Dmitry; Maleki, Lute

2009-01-01

A photonic instrument is proposed to boost the resolution for ultraviolet/ optical/infrared spectral analysis and spectral imaging allowing the detection of narrow (0.00007-to-0.07-picometer wavelength resolution range) optical spectral signatures of chemical elements in space and planetary atmospheres. The idea underlying the proposal is to exploit the advantageous spectral characteristics of whispering-gallery-mode (WGM) resonators to obtain spectral resolutions at least three orders of magnitude greater than those of optical spectrum analyzers now in use. Such high resolutions would enable measurement of spectral features that could not be resolved by prior instruments.

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, D. R.; van Dyk, S. D., Makowiecki, W.; Stauffer, J.; Song, I.; Ro, J.; Fajardo-Acosta, S.; Hoard, D. W.; Wachter, S.

2011-11-01

We present the Spitzer Atlas of Stellar Spectra (SASS), which includes 159 stellar spectra (5 to 32 micron; R about 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, like blue stragglers and certain pulsating variables. All the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, dominated by Hydrogen lines around A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases PAH features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

Surface materials map of Afghanistan: iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Kokaly, Raymond F.; Hoefen, Todd M.; Dudek, Kathleen B.; Livo, Keith E.

2012-01-01

This map shows the distribution of selected iron-bearing minerals and other materials derived from analysis of HyMap imaging spectrometer data of Afghanistan. Using a NASA (National Aeronautics and Space Administration) WB-57 aircraft flown at an altitude of ~15,240 meters or ~50,000 feet, 218 flight lines of data were collected over Afghanistan between August 22 and October 2, 2007. The HyMap data were converted to apparent surface reflectance, then further empirically adjusted using ground-based reflectance measurements. The reflectance spectrum of each pixel of HyMap data was compared to the spectral features of reference entries in a spectral library of minerals, vegetation, water, ice, and snow. This map shows the spatial distribution of iron-bearing minerals and other materials having diagnostic absorptions at visible and near-infrared wavelengths. These absorptions result from electronic processes in the minerals. Several criteria, including (1) the reliability of detection and discrimination of minerals using the HyMap spectrometer data, (2) the relative abundance of minerals, and (3) the importance of particular minerals to studies of Afghanistan's natural resources, guided the selection of entries in the reference spectral library and, therefore, guided the selection of mineral classes shown on this map. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having similar spectral features were less easily discriminated, especially where the minerals were not particularly abundant and (or) where vegetation cover reduced the absorption strength of mineral features. Complications in reflectance calibration also affected the detection and identification of minerals.

Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players

NASA Astrophysics Data System (ADS)

Murugesan, Gowtham; Saghafi, Behrouz; Davenport, Elizabeth; Wagner, Ben; Urban, Jillian; Kelley, Mireille; Jones, Derek; Powers, Alex; Whitlow, Christopher; Stitzel, Joel; Maldjian, Joseph; Montillo, Albert

2018-02-01

The effect of repetitive sub-concussive head impact exposure in contact sports like American football on brain health is poorly understood, especially in the understudied populations of youth and high school players. These players, aged 9-18 years old may be particularly susceptible to impact exposure as their brains are undergoing rapid maturation. This study helps fill the void by quantifying the association between head impact exposure and functional connectivity, an important aspect of brain health measurable via resting-state fMRI (rs-fMRI). The contributions of this paper are three fold. First, the data from two separate studies (youth and high school) are combined to form a high-powered analysis with 60 players. These players experience head acceleration within overlapping impact exposure making their combination particularly appropriate. Second, multiple features are extracted from rs-fMRI and tested for their association with impact exposure. One type of feature is the power spectral density decomposition of intrinsic, spatially distributed networks extracted via independent components analysis (ICA). Another feature type is the functional connectivity between brain regions known often associated with mild traumatic brain injury (mTBI). Third, multiple supervised machine learning algorithms are evaluated for their stability and predictive accuracy in a low bias, nested cross-validation modeling framework. Each classifier predicts whether a player sustained low or high levels of head impact exposure. The nested cross validation reveals similarly high classification performance across the feature types, and the Support Vector, Extremely randomized trees, and Gradboost classifiers achieve F1-score up to 75%.

Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.

2017-12-01

Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of selected IMF, we discern planet bearing fault reasons according to the present peaks. The proposed spectral negentropy infogram based spectrum and demodulation analysis method is illustrated via a numerical simulated signal analysis. Considering the unique load bearing feature of planet bearings, experimental validations under both no-load and loading conditions are done to verify the derived fault symptoms and the proposed method. The localized faults on outer race, rolling element and inner race are successfully diagnosed.

Spectral Domain RF Fingerprinting for 802.11 Wireless Devices

DTIC Science & Technology

2010-03-01

induce unintentional modulation effects . If these effects (features) are sufficiently unique, it becomes possible to identify a device us- ing its...Previous AFIT research has demonstrated the effectiveness of RF Fin- gerprinting using 802.11A signals with 1) spectral correlation on Power Spectral...32 4.5. SD Intra-manufacturer Classification: Effects of Burst Location Error

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

PubMed

Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

2017-01-01

Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

Comparative study of icy patches on comet nuclei

NASA Astrophysics Data System (ADS)

Oklay, Nilda; Pommerol, Antoine; Barucci, Maria Antonietta; Sunshine, Jessica; Sierks, Holger; Pajola, Maurizio

2016-07-01

Cometary missions Deep Impact, EPOXI and Rosetta investigated the nuclei of comets 9P/Tempel 1, 103P/Hartley 2 and 67P/Churyumov-Gerasimenko respectively. Bright patches were observed on the surfaces of each of these three comets [1-5]. Of these, the surface of 67P is mapped at the highest spatial resolution via narrow angle camera (NAC) of the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS, [6]) on board the Rosetta spacecraft. OSIRIS NAC is equipped with twelve filters covering the wavelength range of 250 nm to 1000 nm. Various filters combinations are used during surface mapping. With high spatial resolution data of comet 67P, three types of bright features were detected on the comet surface: Clustered, isolated and bright boulders [2]. In the visible spectral range, clustered bright features on comet 67P display bluer spectral slopes than the average surface [2, 4] while isolated bright features on comet 67P have flat spectra [4]. Icy patches observed on the surface of comets 9P and 103P display bluer spectral slopes than the average surface [1, 5]. Clustered and isolated bright features are blue in the RGB composites generated by using the images taken in NIR, visible and NUV wavelengths [2, 4]. This is valid for the icy patches observed on comets 9P and 103P [1, 5]. Spectroscopic observations of bright patches on comets 9P and 103P confirmed the existence of water [1, 5]. There were more than a hundred of bright features detected on the northern hemisphere of comet 67P [2]. Analysis of those features from both multispectral data and spectroscopic data is an ongoing work. Water ice is detected in eight of the bright features so far [7]. Additionally, spectroscopic observations of two clustered bright features on the surface of comet 67P revealed the existence of water ice [3]. The spectral properties of one of the icy patches were studied by [4] using OSIRIS NAC images and compared with the spectral properties of the active regions observed on comet 67P. Additionally jets rising from the same clustered bright feature were detected visually [4]. We analyzed bright patches on the surface of comets 9P, 103P and 67P using multispectral data obtained by the high-resolution instrument (HRI), medium- resolution instrument (MRI) and OSIRIS NAC using various spectral analysis techniques. Clustered bright features on comet 67P have similar visible spectra to the bright patches on comets 9P and 103P. The comparison of the bright patches includes the published results of the IR spectra. References: [1] Sunshine et al., 2006, Science, 311, 1453 [2] Pommerol et al., 2015, A&A, 583, A25 [3] Filacchione et al., 2016, Nature, 529, 368-372 [4] Oklay et al., 2016, A&A, 586, A80 [5] Sunshine et al. 2012, ACM [6] Keller et al., 2007, Space Sci. Rev., 128, 433 [7] Barucci et al., 2016, COSPAR, B04

National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

PubMed

Waldner, François; Hansen, Matthew C; Potapov, Peter V; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information

PubMed Central

Hansen, Matthew C.; Potapov, Peter V.; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring. PMID:28817618

Configuration of Pluto's Volatile Ices

NASA Astrophysics Data System (ADS)

Grundy, William M.; Binzel, R. P.; Cook, J. C.; Cruikshank, D. P.; Dalle Ore, C. M.; Earle, A. M.; Ennico, K.; Jennings, D. E.; Howett, C. J. A.; Linscott, I. R.; Lunsford, A. W.; Olkin, C. B.; Parker, A. H.; Parker, J. Wm; Protopapa, S.; Reuter, D. C.; Singer, K. N.; Spencer, J. R.; Stern, S. A.; Tsang, C. C. C.; Verbiscer, A. J.; Weaver, H. A.; Young, L. A.; Berry, K.; Buie, M. W.; Stansberry, J. A.

2015-11-01

We report on near-infrared remote sensing by New Horizons' Ralph instrument (Reuter et al. 2008, Space Sci. Rev. 140, 129-154) of Pluto's N2, CO, and CH4 ices. These especially volatile ices are mobile even at Pluto's cryogenic surface temperatures. Sunlight reflected from these ices becomes imprinted with their characteristic spectral absorption bands. The detailed appearance of these absorption features depends on many aspects of local composition, thermodynamic state, and texture. Multiple-scattering radiative transfer models are used to retrieve quantitative information about these properties and to map how they vary across Pluto's surface. Using parameter maps derived from New Horizons observations, we investigate the striking regional differences in the abundances and scattering properties of Pluto's volatile ices. Comparing these spatial patterns with the underlying geology provides valuable constraints on processes actively modifying the planet's surface, over a variety of spatial scales ranging from global latitudinal patterns to more regional and local processes within and around the feature informally known as Sputnik Planum. This work was supported by the NASA New Horizons Project.

Satellite Image Analysis along the Kuala Selangor to Sabak Bernam Rural Tourism Routes

NASA Astrophysics Data System (ADS)

Ibrahim, I.; Zakariya, K.; Wahab, N. A.

2018-02-01

This research focuses on the analysis of land cover map using satellite imagery along the rural routes. The aim of this research is to study the landscape features that can be seen by the tourists around the rural routes. The objectives of the study are twofold: (i) to analyse the land cover types along the rural routes and (ii) to create a tourist map along the rural routes. The method adopted was to use Supervised Classification by creating multiple polygons to ensure that each information is sufficient to create appropriate spectral signatures. The finding shows that 80% of the landscape features along the Point of Interest (POI) are paddy field. According to the analysis using the indicators criteria for choosing the rural routes, this research shows that this area has the potential to be part of a tourism area because it has many historical and cultural elements that can be exposed to tourists. Future research will be a factor analysis on the significance of the criteria to rural tourism attraction.

Raman spectral signatures as conformational probes of gas phase flexible molecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-07-01

A novel application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase flexible molecule is reported. The Raman spectral signatures of four conformers of 2-phenylethylamine are well matched by the results of density functional theory calculations, showing bands uniquely identifying the structures. The measurement of spectral signatures by ILSRS in an extended spectral range, with a conventional laser source, is instrumental in facilitating the unraveling of intra- and intermolecular interactions that are significant in biological structure and activity.

Mass selective separation applied to radioisotopes of cesium: Mass selective applied to radioisotopes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dion, Michael; Eiden, Greg; Farmer, Orville

2016-07-22

A developed technique that uses the intrinsic mass-based separation capability of a quadrupole mass spectrometer has been used to resolve spectral radiometric interference of two isotopes of the same element. In this work the starting sample was a combination of 137Cs and 134Cs and was (activity) dominated by 137Cs and this methodology separated and “implanted” 134Cs that was later quantified for spectral features and ac- tivity with traditional radiometric techniques. This work demonstrated a 134Cs/137Cs activity ratio enhancement of >4 orders of magnitude and complete removal of 137Cs spectral features from the implanted target mass (i.e., 134).

X-Ray Spectra from MHD Simulations of Accreting Black Holes

NASA Technical Reports Server (NTRS)

Schnittman, Jeremy D.; Noble, Scott C.; Krolik, Julian H.

2011-01-01

We present new global calculations of X-ray spectra from fully relativistic magneto-hydrodynamic (MHO) simulations of black hole (BH) accretion disks. With a self consistent radiative transfer code including Compton scattering and returning radiation, we can reproduce the predominant spectral features seen in decades of X-ray observations of stellar-mass BHs: a broad thermal peak around 1 keV, power-law continuum up to >100 keV, and a relativistically broadened iron fluorescent line. By varying the mass accretion rate, different spectral states naturally emerge: thermal-dominant, steep power-law, and low/hard. In addition to the spectral features, we briefly discuss applications to X-ray timing and polarization.

Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm

NASA Astrophysics Data System (ADS)

Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael; Berk, Alexander; Anderson, Gail; Gardner, James; Felde, Gerald

2005-10-01

Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.

Extending a Tandem Mass Spectral Library to Include MS2 Spectra of Fragment Ions Produced In-Source and MSn Spectra.

PubMed

Yang, Xiaoyu; Neta, Pedatsur; Stein, Stephen E

2017-11-01

Tandem mass spectral library searching is finding increased use as an effective means of determining chemical identity in mass spectrometry-based omics studies. We previously reported on constructing a tandem mass spectral library that includes spectra for multiple precursor ions for each analyte. Here we report our method for expanding this library to include MS 2 spectra of fragment ions generated during the ionization process (in-source fragment ions) as well as MS 3 and MS 4 spectra. These can assist the chemical identification process. A simple density-based clustering algorithm was used to cluster all significant precursor ions from MS 1 scans for an analyte acquired during an infusion experiment. The MS 2 spectra associated with these precursor ions were grouped into the same precursor clusters. Subsequently, a new top-down hierarchical divisive clustering algorithm was developed for clustering the spectra from fragmentation of ions in each precursor cluster, including the MS 2 spectra of the original precursors and of the in-source fragments as well as the MS n spectra. This algorithm starts with all the spectra of one precursor in one cluster and then separates them into sub-clusters of similar spectra based on the fragment patterns. Herein, we describe the algorithms and spectral evaluation methods for extending the library. The new library features were demonstrated by searching the high resolution spectra of E. coli extracts against the extended library, allowing identification of compounds and their in-source fragment ions in a manner that was not possible before. Graphical Abstract ᅟ.

On lamps, walls, and eyes: The spectral radiance field and the evaluation of light pollution indoors

NASA Astrophysics Data System (ADS)

Bará, Salvador; Escofet, Jaume

2018-01-01

Light plays a key role in the regulation of different physiological processes, through several visual and non-visual retinal phototransduction channels whose basic features are being unveiled by recent research. The growing body of evidence on the significance of these effects has sparked a renewed interest in the determination of the light field at the entrance pupil of the eye in indoor spaces. Since photic interactions are strongly wavelength-dependent, a significant effort is being devoted to assess the relative merits of the spectra of the different types of light sources available for use at home and in the workplace. The spectral content of the light reaching the observer eyes in indoor spaces, however, does not depend exclusively on the sources: it is partially modulated by the spectral reflectance of the walls and surrounding surfaces, through the multiple reflections of the light beams along all possible paths from the source to the observer. This modulation can modify significantly the non-visual photic inputs that would be produced by the lamps alone, and opens the way for controlling-to a certain extent-the subject's exposure to different regions of the optical spectrum. In this work we evaluate the expected magnitude of this effect and we show that, for factorizable sources, the spectral modulation can be conveniently described in terms of a set of effective filter-like functions that provide useful insights for lighting design and light pollution assessment. The radiance field also provides a suitable bridge between indoor and outdoor light pollution studies.

Near-infrared spectra of the Martian surface: Reading between the lines

NASA Technical Reports Server (NTRS)

Crisp, D.; Bell, J. F., III

1993-01-01

Moderate-resolution near-infrared (NIR) spectra of Mars have been widely used in studies of the Martian surface because many candidate surface materials have distinctive absorption features at these wavelengths. Recent advances in NIR detector technology and instrumentation have also encouraged studies in this spectral region. The use of moderate spectral resolution has often been justified for NIR surface observations because the spectral features produced by most surface materials are relatively broad, and easily discriminated at this resolution. In spite of this, NIR spectra of Mars are usually very difficult to interpret quantitatively. One problem is that NIR surface absorption features are often only a few percent deep, requiring observations with great signal-to-noise ratios. A more significant problem is that gases in the Martian atmosphere contribute numerous absorption features at these wavelengths. Ground-based observers must also contend with variable absorption by several gases in the Earth's atmosphere (H2O, CO2, O3, N2O, CH4, O2). The strong CO2 bands near 1.4, 1.6, 2.0, 2.7, 4.3, and 4.8 micrometers largely preclude the analysis of surface spectral features at these wavelengths. Martian atmospheric water vapor also contributes significant absorption near 1.33, 1.88, and 2.7 micrometers, but water vapor in the Earth's atmosphere poses a much larger problem to ground-based studies of these spectral regions. The third most important NIR absorber in the Martian atmosphere is CO. This gas absorbs most strongly in the relatively-transparent spectral windows near 4.6 and 2.3 micrometers. It also produces 1-10 percent absorption in the solar spectrum at these NIR wavelengths. This solar CO absorption cannot be adequately removed by dividing the Martian spectrum by that of a star, as is commonly done to calibrate ground-based spectroscopic observations, because most stars do not have identical amounts of CO absorption in their spectra. Here, we describe tow effective methods for eliminating contamination of Martian surface spectra by absorption in the solar, terrestrial, and Martian atmospheres. Both methods involve the use of very-high-resolution spectra that completely resolve the narrow atmospheric absorption lines.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions

PubMed Central

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions. PMID:28700720

Musical ability and non-native speech-sound processing are linked through sensitivity to pitch and spectral information.

PubMed

Kempe, Vera; Bublitz, Dennis; Brooks, Patricia J

2015-05-01

Is the observed link between musical ability and non-native speech-sound processing due to enhanced sensitivity to acoustic features underlying both musical and linguistic processing? To address this question, native English speakers (N = 118) discriminated Norwegian tonal contrasts and Norwegian vowels. Short tones differing in temporal, pitch, and spectral characteristics were used to measure sensitivity to the various acoustic features implicated in musical and speech processing. Musical ability was measured using Gordon's Advanced Measures of Musical Audiation. Results showed that sensitivity to specific acoustic features played a role in non-native speech-sound processing: Controlling for non-verbal intelligence, prior foreign language-learning experience, and sex, sensitivity to pitch and spectral information partially mediated the link between musical ability and discrimination of non-native vowels and lexical tones. The findings suggest that while sensitivity to certain acoustic features partially mediates the relationship between musical ability and non-native speech-sound processing, complex tests of musical ability also tap into other shared mechanisms. © 2014 The British Psychological Society.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

NASA Astrophysics Data System (ADS)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions.

PubMed

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro; Rey, Beatriz

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.

Fluorescent marker-based and marker-free discrimination between healthy and cancerous human tissues using hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2015-06-01

Two problems are addressed in this paper (i) the fluorescent marker-based and the (ii) marker-free discrimination between healthy and cancerous human tissues. For both applications the performance of hyper-spectral methods are quantified. Fluorescent marker-based tissue classification uses a number of fluorescent markers to dye specific parts of a human cell. The challenge is that the emission spectra of the fluorescent dyes overlap considerably. They are, furthermore disturbed by the inherent auto-fluorescence of human tissue. This results in ambiguities and decreased image contrast causing difficulties for the treatment decision. The higher spectral resolution introduced by tunable-filter-based spectral imaging in combination with spectral unmixing techniques results in an improvement of the image contrast and therefore more reliable information for the physician to choose the treatment decision. Marker-free tissue classification is based solely on the subtle spectral features of human tissue without the use of artificial markers. The challenge in this case is that the spectral differences between healthy and cancerous tissues are subtle and embedded in intra- and inter-patient variations of these features. The contributions of this paper are (i) the evaluation of hyper-spectral imaging in combination with spectral unmixing techniques for fluorescence marker-based tissue classification, (ii) the evaluation of spectral imaging for marker-free intra surgery tissue classification. Within this paper, we consider real hyper-spectral fluorescence and endoscopy data sets to emphasize the practical capability of the proposed methods. It is shown that the combination of spectral imaging with multivariate statistical methods can improve the sensitivity and specificity of the detection and the staging of cancerous tissues compared to standard procedures.

Vowel reduction in word-final position by early and late Spanish-English bilinguals.

PubMed

Byers, Emily; Yavas, Mehmet

2017-01-01

Vowel reduction is a prominent feature of American English, as well as other stress-timed languages. As a phonological process, vowel reduction neutralizes multiple vowel quality contrasts in unstressed syllables. For bilinguals whose native language is not characterized by large spectral and durational differences between tonic and atonic vowels, systematically reducing unstressed vowels to the central vowel space can be problematic. Failure to maintain this pattern of stressed-unstressed syllables in American English is one key element that contributes to a "foreign accent" in second language speakers. Reduced vowels, or "schwas," have also been identified as particularly vulnerable to the co-articulatory effects of adjacent consonants. The current study examined the effects of adjacent sounds on the spectral and temporal qualities of schwa in word-final position. Three groups of English-speaking adults were tested: Miami-based monolingual English speakers, early Spanish-English bilinguals, and late Spanish-English bilinguals. Subjects performed a reading task to examine their schwa productions in fluent speech when schwas were preceded by consonants from various points of articulation. Results indicated that monolingual English and late Spanish-English bilingual groups produced targeted vowel qualities for schwa, whereas early Spanish-English bilinguals lacked homogeneity in their vowel productions. This extends prior claims that schwa is targetless for F2 position for native speakers to highly-proficient bilingual speakers. Though spectral qualities lacked homogeneity for early Spanish-English bilinguals, early bilinguals produced schwas with near native-like vowel duration. In contrast, late bilinguals produced schwas with significantly longer durations than English monolinguals or early Spanish-English bilinguals. Our results suggest that the temporal properties of a language are better integrated into second language phonologies than spectral qualities. Finally, we examined the role of nonstructural variables (e.g. linguistic history measures) in predicting native-like vowel duration. These factors included: Age of L2 learning, amount of L1 use, and self-reported bilingual dominance. Our results suggested that different sociolinguistic factors predicted native-like reduced vowel duration than predicted native-like vowel qualities across multiple phonetic environments.

Vowel reduction in word-final position by early and late Spanish-English bilinguals

PubMed Central

2017-01-01

Vowel reduction is a prominent feature of American English, as well as other stress-timed languages. As a phonological process, vowel reduction neutralizes multiple vowel quality contrasts in unstressed syllables. For bilinguals whose native language is not characterized by large spectral and durational differences between tonic and atonic vowels, systematically reducing unstressed vowels to the central vowel space can be problematic. Failure to maintain this pattern of stressed-unstressed syllables in American English is one key element that contributes to a “foreign accent” in second language speakers. Reduced vowels, or “schwas,” have also been identified as particularly vulnerable to the co-articulatory effects of adjacent consonants. The current study examined the effects of adjacent sounds on the spectral and temporal qualities of schwa in word-final position. Three groups of English-speaking adults were tested: Miami-based monolingual English speakers, early Spanish-English bilinguals, and late Spanish-English bilinguals. Subjects performed a reading task to examine their schwa productions in fluent speech when schwas were preceded by consonants from various points of articulation. Results indicated that monolingual English and late Spanish-English bilingual groups produced targeted vowel qualities for schwa, whereas early Spanish-English bilinguals lacked homogeneity in their vowel productions. This extends prior claims that schwa is targetless for F2 position for native speakers to highly-proficient bilingual speakers. Though spectral qualities lacked homogeneity for early Spanish-English bilinguals, early bilinguals produced schwas with near native-like vowel duration. In contrast, late bilinguals produced schwas with significantly longer durations than English monolinguals or early Spanish-English bilinguals. Our results suggest that the temporal properties of a language are better integrated into second language phonologies than spectral qualities. Finally, we examined the role of nonstructural variables (e.g. linguistic history measures) in predicting native-like vowel duration. These factors included: Age of L2 learning, amount of L1 use, and self-reported bilingual dominance. Our results suggested that different sociolinguistic factors predicted native-like reduced vowel duration than predicted native-like vowel qualities across multiple phonetic environments. PMID:28384234

Object-based Landslide Mapping: Examples, Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Hölbling, Daniel; Eisank, Clemens; Friedl, Barbara; Chang, Kang-Tsung; Tsai, Tsai-Tsung; Birkefeldt Møller Pedersen, Gro; Betts, Harley; Cigna, Francesca; Chiang, Shou-Hao; Aubrey Robson, Benjamin; Bianchini, Silvia; Füreder, Petra; Albrecht, Florian; Spiekermann, Raphael; Weinke, Elisabeth; Blaschke, Thomas; Phillips, Chris

2016-04-01

Over the last decade, object-based image analysis (OBIA) has been increasingly used for mapping landslides that occur after triggering events such as heavy rainfall. The increasing availability and quality of Earth Observation (EO) data in terms of temporal, spatial and spectral resolution allows for comprehensive mapping of landslides at multiple scales. Most often very high resolution (VHR) or high resolution (HR) optical satellite images are used in combination with a digital elevation model (DEM) and its products such as slope and curvature. Semi-automated object-based mapping makes use of various characteristics of image objects that are derived through segmentation. OBIA enables numerous spectral, spatial, contextual and textural image object properties to be applied during an analysis. This is especially useful when mapping complex natural features such as landslides and constitutes an advantage over pixel-based image analysis. However, several drawbacks in the process of object-based landslide mapping have not been overcome yet. The developed classification routines are often rather complex and limited regarding their transferability across areas and sensors. There is still more research needed to further improve present approaches and to fully exploit the capabilities of OBIA for landslide mapping. In this study several examples of object-based landslide mapping from various geographical regions with different characteristics are presented. Examples from the Austrian and Italian Alps are shown, whereby one challenge lies in the detection of small-scale landslides on steep slopes while preventing the classification of false positives with similar spectral properties (construction areas, utilized land, etc.). Further examples feature landslides mapped in Iceland, where the differentiation of landslides from other landscape-altering processes in a highly dynamic volcanic landscape poses a very distinct challenge, and in Norway, which is exposed to multiple types of landslides. Unlike in these northern European countries, landslides in Taiwan can be effectively delineated based on spectral differences as the surrounding is most often densely vegetated. In this tropical/subtropical region the fast information provision after Typhoon events is important. This need can be addressed in OBIA by automatically calculating thresholds based on vegetation indices and using them for a first rough identification of areas affected by landslides. Moreover, the differentiation in landslide source and transportation area is of high relevance in Taiwan. Finally, an example from New Zealand, where landslide inventory mapping is important for estimating surface erosion, will demonstrate the performance of OBIA compared to visual expert interpretation and on-screen mapping. The associated challenges and opportunities related to case studies in each of these regions are discussed and reviewed. In doing so, open research issues in object-based landslide mapping based on EO data are identified and highlighted.

Advances in structure elucidation of small molecules using mass spectrometry

PubMed Central

Fiehn, Oliver

2010-01-01

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules. Electronic supplementary material The online version of this article (doi:10.1007/s12566-010-0015-9) contains supplementary material, which is available to authorized users. PMID:21289855

Optical spectral singularities as threshold resonances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mostafazadeh, Ali

2011-04-15

Spectral singularities are among generic mathematical features of complex scattering potentials. Physically they correspond to scattering states that behave like zero-width resonances. For a simple optical system, we show that a spectral singularity appears whenever the gain coefficient coincides with its threshold value and other parameters of the system are selected properly. We explore a concrete realization of spectral singularities for a typical semiconductor gain medium and propose a method of constructing a tunable laser that operates at threshold gain.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

High-resolution CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites

USGS Publications Warehouse

Jaumann, R.; Stephan, K.; Brown, R.H.; Buratti, B.J.; Clark, R.N.; McCord, T.B.; Coradini, A.; Capaccioni, F.; Filacchione, G.; Cerroni, P.; Baines, K.H.; Bellucci, G.; Bibring, J.-P.; Combes, M.; Cruikshank, D.P.; Drossart, P.; Formisano, V.; Langevin, Y.; Matson, D.L.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Soderbloom, L.A.; Griffith, C.; Matz, K.-D.; Roatsch, Th.; Scholten, F.; Porco, C.C.

2006-01-01

The Visual Infrared Mapping Spectrometer (VIMS) onboard the CASSINI spacecraft obtained new spectral data of the icy satellites of Saturn after its arrival at Saturn in June 2004. VIMS operates in a spectral range from 0.35 to 5.2 ??m, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. As an imaging spectrometer VIMS combines the characteristics of both a spectrometer and an imaging instrument. This makes it possible to analyze the spectrum of each pixel separately and to map the spectral characteristics spatially, which is important to study the relationships between spectral information and geological and geomorphologic surface features. The spatial analysis of the spectral data requires the determination of the exact geographic position of each pixel on the specific surface and that all 352 spectral elements of each pixel show the same region of the target. We developed a method to reproject each pixel geometrically and to convert the spectral data into map projected image cubes. This method can also be applied to mosaic different VIMS observations. Based on these mosaics, maps of the spectral properties for each Saturnian satellite can be derived and attributed to geographic positions as well as to geological and geomorphologic surface features. These map-projected mosaics are the basis for all further investigations. ?? 2006 Elsevier Ltd. All rights reserved.

Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

NASA Astrophysics Data System (ADS)

Tang, Hong; Lin, Jian-Zhong

2013-01-01

An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data.

Pulsational mode fluctuations and their basic conservation laws

NASA Astrophysics Data System (ADS)

Borah, B.; Karmakar, P. K.

2015-01-01

We propose a theoretical hydrodynamic model for investigating the basic features of nonlinear pulsational mode stability in a partially charged dust molecular cloud within the framework of the Jeans homogenization assumption. The inhomogeneous cloud is modeled as a quasi-neutral multifluid consisting of the warm electrons, warm ions, and identical inertial cold dust grains with partial ionization in a neutral gaseous background. The grain-charge is assumed not to vary in the fluctuation evolution time scale. The active inertial roles of the thermal species are included. We apply a standard multiple scaling technique centered on the gravito-electrostatic equilibrium to understand the fluctuations on the astrophysical scales of space and time. This is found that electrostatic and self-gravitational eigenmodes co-exist as diverse solitary spectral patterns governed by a pair of Korteweg-de Vries (KdV) equations. In addition, all the relevant classical conserved quantities associated with the KdV system under translational invariance are methodologically derived and numerically analyzed. A full numerical shape-analysis of the fluctuations, scale lengths and perturbed densities with multi-parameter variation of judicious plasma conditions is carried out. A correlation of the perturbed densities and gravito-electrostatic spectral patterns is also graphically indicated. It is demonstrated that the solitary mass, momentum and energy densities also evolve like solitary spectral patterns which remain conserved throughout the spatiotemporal scales of the fluctuation dynamics. Astrophysical and space environments significant to our results are briefly highlighted.

Predictive value of dual-energy spectral computed tomographic imaging on the histological origin of carcinomas in the ampullary region.

PubMed

Wei, Wei; Yu, Yongqiang; Lv, Weifu; Deng, Kexue; Yuan, Lei; Zhao, Yingming

2014-08-01

To investigate the value of dual-energy spectral computed tomographic imaging (DESCT) to predict the origin of carcinomas in the ampullary region. Fifty-seven patients with suspected ampullary region carcinomas underwent DESCT prior to biopsy or surgery. Among those patients, 30 were pancreatic adenocarcinomas, 11 were biliary adenocarcinomas, 16 were adenocarcinomas of the ampulla diagnosed by biopsy and/or pathological examination before or after surgical operation. We compared the CT spectral imaging features among the adenocarcinomas with the above-mentioned three different origins. Iodine concentration thresholds of 16.36, 21.86, and 21.86 mg/mL yielded a sensitivity and specificity of 100% for distinguishing between common bile duct adenocarcinomas and pancreatic adenocarcinomas in the arterial phase (AP), portal venous phase (PP), and delayed phase (DP), respectively. Thresholds of 16.70, 24.33, and 26.43 mg/mL yielded a sensitivity and specificity of 100% for distinguishing between common bile duct adenocarcinomas and ampullary adenocarcinomas in the AP, PP, and DP, respectively. Iodine concentration thresholds of 16.66 and 17.78 mg/mL yielded a sensitivity and specificity of 100% for distinguishing between ampullary adenocarcinomas and pancreatic adenocarcinomas in the PP and DP, respectively. DESCT with multiple parameters can provide useful diagnostic information and may be used to predict the histological origin of carcinomas in the ampullary region.

VEGAS: VErsatile GBT Astronomical Spectrometer

NASA Astrophysics Data System (ADS)

Bussa, Srikanth; VEGAS Development Team

2012-01-01

The National Science Foundation Advanced Technologies and Instrumentation (NSF-ATI) program is funding a new spectrometer backend for the Green Bank Telescope (GBT). This spectrometer is being built by the CICADA collaboration - collaboration between the National Radio Astronomy Observatory (NRAO) and the Center for Astronomy Signal Processing and Electronics Research (CASPER) at the University of California Berkeley.The backend is named as VErsatile GBT Astronomical Spectrometer (VEGAS) and will replace the capabilities of the existing spectrometers. This backend supports data processing from focal plane array systems. The spectrometer will be capable of processing up to 1.25 GHz bandwidth from 8 dual polarized beams or a bandwidth up to 10 GHz from a dual polarized beam.The spectrometer will be using 8-bit analog to digital converters (ADC), which gives a better dynamic range than existing GBT spectrometers. There will be 8 tunable digital sub-bands within the 1.25 GHz bandwidth, which will enhance the capability of simultaneous observation of multiple spectral transitions. The maximum spectral dump rate to disk will be about 0.5 msec. The vastly enhanced backend capabilities will support several science projects with the GBT. The projects include mapping temperature and density structure of molecular clouds; searches for organic molecules in the interstellar medium; determination of the fundamental constants of our evolving Universe; red-shifted spectral features from galaxies across cosmic time and survey for pulsars in the extreme gravitational environment of the Galactic Center.

IMAGING SPECTROSCOPY FOR DETERMINING RANGELAND STRESSORS TO WESTERN WATERSHEDS

EPA Science Inventory

The Environmental Protection Agency is developing rangeland ecological indicators in twelve western states using advanced remote sensing techniques. Fine spectral resolution (hyperspectral) sensors, or imaging spectrometers, can detect the subtle spectral features that make veget...

IMAGING SPECTROSCOPY FOR DETERMINING RANGELAND STRESSORS TO WESTERN WATERSHEDS

EPA Science Inventory

The Environmental Protection Agency is developing rangeland ecological indicators in eleven western states using advanced remote sensing systems. Fine spectral resolution (hyperspemal) sensors, or imaging spectrometers, can detect the subtle spectral features that makes vegetatio...

Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

NASA Astrophysics Data System (ADS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

2010-05-01

Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection was suggested. On the basis of analyzing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from remote sensing data was discussed. Spectral signatures of different terrain features have been used to extract structural patterns aiming to separate surface units and to classify the general categories. The synergetic analysis and interpretation of the different satellite images (LANDSAT: TM, ETM; MODIS, IKONOS) acquired over a period of more than 20 years reveals significant aspects regarding impacts of climate and anthropogenic changes on urban/periurban environment. It was delimited residential zones of industrial zones which are very often a source of pollution. An important role has urban green cover assessment. Have been emphasized the particularities of the functional zones from different points of view: architectural, streets and urban surface traffic, some components of urban infrastructure as well as habitat quality. The growth of Bucharest urban area in Romania has been a result of a rapid process of industrialization, and also of the increase of urban population. Information on the spatial pattern and temporal dynamics of land cover and land use of urban areas is critical to address a wide range of practical problems relating to urban regeneration, urban sustainability and rational planning policy.

Analysis of cosmetic residues on a single human hair by ATR FT-IR microspectroscopy

NASA Astrophysics Data System (ADS)

Pienpinijtham, Prompong; Thammacharoen, Chuchaat; Naranitad, Suwimol; Ekgasit, Sanong

2018-05-01

In this work, ATR FT-IR spectra of single human hair and cosmetic residues on hair surface are successfully collected using a homemade dome-shaped Ge μIRE accessary installed on an infrared microscope. By collecting ATR spectra of hairs from the same person, the spectral patterns are identical and superimposed while different spectral features are observed from ATR spectra of hairs collected from different persons. The spectral differences depend on individual hair characteristics, chemical treatments, and cosmetics on hair surface. The "Contact-and-Collect" technique that transfers remarkable materials on the hair surface to the tip of the Ge μIRE enables an identification of cosmetics on a single hair. Moreover, the differences between un-split and split hairs are also studied in this report. These highly specific spectral features can be employed for unique identification or for differentiation of hairs based on the molecular structures of hairs and cosmetics on hairs.

Formation of spectral lines in planetary atmospheres. I - Theory for cloudy atmospheres: Application to Venus.

NASA Technical Reports Server (NTRS)

Hunt, G. E.

1972-01-01

The theory of the formation of spectral lines in a cloudy planetary atmosphere is studied in detail. It is shown that models based upon homogeneous, isotropically scattering atmospheres cannot be used to reproduce observed spectroscopic features of phase effect and the shape of spectral lines for weak and strong bands. The theory must, therefore, be developed using an inhomogeneous (gravitational) model of a planetary atmosphere, accurately incorporating all the physical processes of radiative transfer. Such a model of the lower Venus atmosphere, consistent with our present knowledge, is constructed. The results discussed in this article demonstrate the effects of the parameters that describe the atmospheric model on the spectroscopic features of spectral line profile and phase effect, at visible and near infrared wavelengths. This information enables us to develop a comprehensive theory of line formation in a Venus atmosphere.

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

NASA Astrophysics Data System (ADS)

Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

2018-04-01

Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

The basal ganglia is necessary for learning spectral, but not temporal features of birdsong

PubMed Central

Ali, Farhan; Fantana, Antoniu L.; Burak, Yoram; Ölveczky, Bence P.

2013-01-01

Executing a motor skill requires the brain to control which muscles to activate at what times. How these aspects of control - motor implementation and timing - are acquired, and whether the learning processes underlying them differ, is not well understood. To address this we used a reinforcement learning paradigm to independently manipulate both spectral and temporal features of birdsong, a complex learned motor sequence, while recording and perturbing activity in underlying circuits. Our results uncovered a striking dissociation in how neural circuits underlie learning in the two domains. The basal ganglia was required for modifying spectral, but not temporal structure. This functional dissociation extended to the descending motor pathway, where recordings from a premotor cortex analogue nucleus reflected changes to temporal, but not spectral structure. Our results reveal a strategy in which the nervous system employs different and largely independent circuits to learn distinct aspects of a motor skill. PMID:24075977

Classification of arrhythmia using hybrid networks.

PubMed

Haseena, Hassan H; Joseph, Paul K; Mathew, Abraham T

2011-12-01

Reliable detection of arrhythmias based on digital processing of Electrocardiogram (ECG) signals is vital in providing suitable and timely treatment to a cardiac patient. Due to corruption of ECG signals with multiple frequency noise and presence of multiple arrhythmic events in a cardiac rhythm, computerized interpretation of abnormal ECG rhythms is a challenging task. This paper focuses a Fuzzy C- Mean (FCM) clustered Probabilistic Neural Network (PNN) and Multi Layered Feed Forward Network (MLFFN) for the discrimination of eight types of ECG beats. Parameters such as fourth order Auto Regressive (AR) coefficients along with Spectral Entropy (SE) are extracted from each ECG beat and feature reduction has been carried out using FCM clustering. The cluster centers form the input of neural network classifiers. The extensive analysis of Massachusetts Institute of Technology- Beth Israel Hospital (MIT-BIH) arrhythmia database shows that FCM clustered PNNs is superior in cardiac arrhythmia classification than FCM clustered MLFFN with an overall accuracy of 99.05%, 97.14%, respectively.

Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond

PubMed Central

Nam, Sung Sik; Alouini, Mohamed-Slim; Choi, Seyeong

2016-01-01

In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment. PMID:27898712

Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond.

PubMed

Nam, Sung Sik; Alouini, Mohamed-Slim; Choi, Seyeong

2016-01-01

In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment.

Spatiotemporal source tuning filter bank for multiclass EEG based brain computer interfaces.

PubMed

Acharya, Soumyadipta; Mollazadeh, Moshen; Murari, Kartikeya; Thakor, Nitish

2006-01-01

Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT) filter bank, each channel of which was tuned to the activity of an underlying dipole source. Changes in the event-related spectral perturbation (ERSP) were measured and used to train a linear support vector machine to classify between four classes of motor imagery tasks (left hand, right hand, foot and tongue) for one subject. ERSP values were significantly (p<0.01) different across tasks and better (p<0.01) than conventional spatial filtering methods (large Laplacian and common average reference). Classification resulted in an average accuracy of 82.5%. This approach could lead to promising BCI applications such as control of a prosthesis with multiple degrees of freedom.

Demonstration of a rapidly-swept external cavity quantum cascade laser for atmospheric sensing applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brumfield, Brian E.; Taubman, Matthew S.; Phillips, Mark C.

2016-07-01

The application of quantum cascade lasers (QCLs) in atmospheric science for trace detection of gases has been demonstrated using sensors in point or remote sensing configurations. Many of these systems utilize single narrowly-tunable (~10 cm-1) distributed feedback (DFB-) QCLs that limit simultaneous detection to a restricted number of small chemical species like H2O or N2O. The narrow wavelength range of DFB-QCLs precludes accurate quantification of large chemical species with broad rotationally-unresolved vibrational spectra, such as volatile organic compounds, that play an important role in the chemistry of the atmosphere. External-cavity (EC-) QCL systems are available that offer tuning ranges >100more » cm-1, making them excellent IR sources for measuring multiple small and large chemical species in the atmosphere. While the broad wavelength coverage afforded by an EC system enables measurements of large chemical species, most commercial systems can only be swept over their entire wavelength range at less than 10 Hz. This prohibits broadband simultaneous measurements of multiple chemicals in plumes from natural or industrial sources where turbulence and/or chemical reactivity are resulting in rapid changes in chemical composition on sub-1s timescales. At Pacific Northwest National Laboratory we have developed rapidly-swept EC-QCL technology that acquires broadband absorption spectra (~100 cm-1) on ms timescales. The spectral resolution of this system has enabled simultaneous measurement of narrow rotationally-resolved atmospherically-broadened lines from small chemical species, while offering the broad tuning range needed to measure broadband spectral features from multiple large chemical species. In this talk the application of this technology for open-path atmospheric measurements will be discussed based on results from laboratory measurements with simulated plumes of chemicals. The performance offered by the system for simultaneous detection of multiple chemical species will be presented.« less

Demonstration of a Rapidly-Swept External Cavity Quantum Cascade Laser for Atmospheric Sensing Applications

NASA Astrophysics Data System (ADS)

Brumfield, Brian E.; Taubman, Matthew S.; Phillips, Mark C.; Suter, Jonathan D.

2016-06-01

The application of quantum cascade lasers (QCLs) in atmospheric science for trace detection of gases has been demonstrated using sensors in point or remote sensing configurations. Many of these systems utilize single narrowly-tunable (˜10 wn) distributed feedback (DFB-) QCLs that limit simultaneous detection to a restricted number of small chemical species like H2O or N2O. The narrow wavelength range of DFB-QCLs precludes accurate quantification of large chemical species with broad rotationally-unresolved vibrational spectra, such as volatile organic compounds, that play an important role in the chemistry of the atmosphere. External-cavity (EC-) QCL systems are available that offer tuning ranges greater than 100 wn, making them excellent IR sources for measuring multiple small and large chemical species in the atmosphere. While the broad wavelength coverage afforded by an EC system enables measurements of large chemical species, most commercial systems can only be swept over their entire wavelength range at less than 10 Hz. This prohibits broadband simultaneous measurements of multiple chemicals in plumes from natural or industrial sources where turbulence and/or chemical reactivity are resulting in rapid changes in chemical composition on sub-1s timescales. At Pacific Northwest National Laboratory we have developed rapidly-swept EC-QCL technology that acquires broadband absorption spectra (˜100 wn) on ms timescales. The spectral resolution of this system has enabled simultaneous measurement of narrow rotationally-resolved atmospherically-broadened lines from small chemical species, while offering the broad tuning range needed to measure broadband spectral features from multiple large chemical species. In this talk the application of this technology for open-path atmospheric measurements will be discussed based on results from laboratory measurements with simulated plumes of chemicals. The performance offered by the system for simultaneous detection of multiple chemical species will be presented. The Pacific Northwest National Laboratory is operated for the U.S. Department of Energy (DOE) by the Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.

Discrimination of poorly exposed lithologies in AVIRIS data

NASA Technical Reports Server (NTRS)

Farrand, William H.; Harsanyi, Joseph C.

1993-01-01

One of the advantages afforded by imaging spectrometers such as AVIRIS is the capability to detect target materials at a sub-pixel scale. This paper presents several examples of the identification of poorly exposed geologic materials - materials which are either subpixel in scale or which, while having some surface expression over several pixels, are partially covered by vegetation or other materials. Sabol et al. (1992) noted that a primary factor in the ability to distinguish sub-pixel targets is the spectral contrast between the target and its surroundings. In most cases, this contrast is best expressed as an absorption feature or features present in the target but absent in the surroundings. Under such circumstances, techniques such as band depth mapping (Clark et al., 1992) are feasible. However, the only difference between a target material and its surroundings is often expressed solely in the continuum. We define the 'continuum' as the reflectance or radiance spanning spectral space between spectral features. Differences in continuum slope and shape can only be determined by reduction techniques which considers the entire spectral range; i.e., techniques such as spectral mixture analysis (Adams et al., 1989) and recently developed techniques which utilize an orthogonal subspace projection operator (Harsanyi, 1993). Two of the three examples considered herein deal with cases where the target material differs from its surroundings only by such a subtle continuum change.

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines

PubMed Central

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J.; Li, Ming

2013-01-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables. PMID:22552787

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines.

PubMed

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J; Li, Ming; Tabb, David L

2012-09-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

NASA Astrophysics Data System (ADS)

Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad

2015-01-01

Palm vein recognition (PVR) is a promising new biometric that has been applied successfully as a method of access control by many organizations, which has even further potential in the field of forensics. The palm vein pattern has highly discriminative features that are difficult to forge because of its subcutaneous position in the palm. Despite considerable progress and a few practical issues, providing accurate palm vein readings has remained an unsolved issue in biometrics. We propose a robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA). As the dimension of WS generated features is quite large, SRKDA is required to reduce the extracted features to enhance the discrimination. The results based on two public databases-PolyU Hyper Spectral Palmprint public database and PolyU Multi Spectral Palmprint-show the high performance of the proposed scheme in comparison with state-of-the-art methods. The proposed approach scored a 99.44% identification rate and a 99.90% verification rate [equal error rate (EER)=0.1%] for the hyperspectral database and a 99.97% identification rate and a 99.98% verification rate (EER=0.019%) for the multispectral database.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

Real-time evaluation of polyphenol oxidase (PPO) activity in lychee pericarp based on weighted combination of spectral data and image features as determined by fuzzy neural network.

PubMed

Yang, Yi-Chao; Sun, Da-Wen; Wang, Nan-Nan; Xie, Anguo

2015-07-01

A novel method of using hyperspectral imaging technique with the weighted combination of spectral data and image features by fuzzy neural network (FNN) was proposed for real-time prediction of polyphenol oxidase (PPO) activity in lychee pericarp. Lychee images were obtained by a hyperspectral reflectance imaging system operating in the range of 400-1000nm. A support vector machine-recursive feature elimination (SVM-RFE) algorithm was applied to eliminating variables with no or little information for the prediction from all bands, resulting in a reduced set of optimal wavelengths. Spectral information at the optimal wavelengths and image color features were then used respectively to develop calibration models for the prediction of PPO in pericarp during storage, and the results of two models were compared. In order to improve the prediction accuracy, a decision strategy was developed based on weighted combination of spectral data and image features, in which the weights were determined by FNN for a better estimation of PPO activity. The results showed that the combined decision model was the best among all of the calibration models, with high R(2) values of 0.9117 and 0.9072 and low RMSEs of 0.45% and 0.459% for calibration and prediction, respectively. These results demonstrate that the proposed weighted combined decision method has great potential for improving model performance. The proposed technique could be used for a better prediction of other internal and external quality attributes of fruits. Copyright © 2015 Elsevier B.V. All rights reserved.

Absorption Efficiencies of Forsterite. I: DDA Explorations in Grain Shape and Size

NASA Technical Reports Server (NTRS)

Lindsay, Sean S.; Wooden, Diane; Harker, David E.; Kelley, Michael S.; Woodward, Charles E.; Murphy, Jim R.

2013-01-01

We compute the absorption efficiency (Q(sub abs)) of forsterite using the discrete dipole approximation (DDA) in order to identify and describe what characteristics of crystal grain shape and size are important to the shape, peak location, and relative strength of spectral features in the 8 - 40 micron wavelength range. Using the DDSCAT code, we compute Q(sub abs) for non-spherical polyhedral grain shapes with a(sub eff) = 0.1 micron. The shape characteristics identified are: 1) elongation/reduction along one of three crystallographic axes; 2) asymmetry, such that all three crystallographic axes are of different lengths; and 3) the presence of crystalline faces that are not parallel to a specific crystallographic axis, e.g., non-rectangular prisms and (di)pyramids. Elongation/reduction dominates the locations and shapes of spectral features near 10, 11, 16, 23.5, 27, and 33.5 micron, while asymmetry and tips are secondary shape effects. Increasing grain sizes (0.1 - 1.0 micron) shifts the 10, 11 micron features systematically towards longer wavelengths and relative to the 11 micron feature increases the strengths and slightly broadens the longer wavelength features. Seven spectral shape classes are established for crystallographic a-, b-, and c-axes and include columnar and platelet shapes plus non-elongated or equant grain shapes. The spectral shape classes and the effects of grain size have practical application in identifying or excluding columnar, platelet or equant forsterite grain shapes in astrophysical environs. Identification of the shape characteristics of forsterite from 8 - 40 micron spectra provides a potential means to probe the temperatures at which forsterite formed.

An electron spin resonance study of gamma-irradiated grapes

NASA Astrophysics Data System (ADS)

Tabner, Brian J.; Tabner, Vivienne A.

The ESR spectra of the seeds, skins and stalks of unirradiated and γ-irradiated Cape black grapes have been obtained. In the spectra of all parts of the grape a single line (g ca. 2.004) is observed both before and after irradiation. New spectral features are observed after irradiation with doses of between 2 and 10 kGy. Some of these features decline in intensity over a period of several days. However, in the case of stalks, new spectral features are readily observed over the shelf-life of the fruit and in samples irradiated to a dose of only 2kGy.

The Copernicus ultraviolet spectral atlas of Sirius

NASA Technical Reports Server (NTRS)

Rogerson, John B., Jr.

1987-01-01

A near-ultraviolet spectral atlas for the A1 V star Alpha CMa (Sirius) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 1649 to 3170 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs, and line identifications for the absorption features have been tabulated.

Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery

USDA-ARS?s Scientific Manuscript database

Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust c...

Development of a new approach based on midwave infrared spectroscopy for post-consumer black plastic waste sorting in the recycling industry.

PubMed

Rozenstein, Offer; Puckrin, Eldon; Adamowski, Jan

2017-10-01

Waste sorting is key to the process of waste recycling. Exact identification of plastic resin and wood products using Near Infrared (NIR, 1-1.7µm) sensing is currently in use. Yet, dark targets characterized by low reflectance, such as black plastics, are hard to identify by this method. Following the recent success of Midwave Infrared (MWIR, 3-12µm) measurements to identify coloured plastic polymers, the aim of this study was to assess whether this technique is applicable to sorting black plastic polymers and wood products. We performed infrared reflectance contact measurements of 234 plastic samples and 29 samples of wood and paper products. Plastic samples included black, coloured and transparent Polyethylene Terephthalate (PET), Polyethylene (PE), Polyvinyl Chloride (PVC), Polypropylene (PP), Polylactic acid (PLA) and Polystyrene (PS). The spectral signatures of the black and coloured plastic samples were compared with clear plastic samples and signatures documented in the literature to identify the polymer spectral features in the presence of coloured material. This information was used to determine the spectral bands that best suit the sorting of black plastic polymers. The main NIR-MWIR absorption features of wood, cardboard and paper were identified as well according to the spectral measurements. Good agreement was found between our measurements and the absorption features documented in the literature. The new approach using MWIR spectral features appears to be useful for black plastics as it overcomes some of the limitations in the NIR region to identify them. The main limitation of this technique for industrial applications is the trade-off between the signal-to-noise ratio of the sensor operating in standoff mode and the speed at which waste is moved under the sensor. This limitation can be resolved by reducing the system's spectral resolution to 16cm -1 , which allows for faster spectra acquisition while maintaining a reasonable signal-to-noise ratio. Copyright © 2017 Elsevier Ltd. All rights reserved.

INSTRUMENTS AND METHODS OF INVESTIGATION: Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

NASA Astrophysics Data System (ADS)

Busarev, Vladimir V.; Prokof'eva-Mikhailovskaya, Valentina V.; Bochkov, Valerii V.

2007-06-01

A method of reflectance spectrophotometry of atmosphereless bodies of the Solar system, its specificity, and the means of eliminating basic spectral noise are considered. As a development, joining the method of reflectance spectrophotometry with the frequency analysis of observational data series is proposed. The combined spectral-frequency method allows identification of formations with distinctive spectral features, and estimations of their sizes and distribution on the surface of atmospherelss celestial bodies. As applied to investigations of asteroids 21 Lutetia and 4 Vesta, the spectral frequency method has given us the possibility of obtaining fundamentally new information about minor planets.

SpecViz: Interactive Spectral Data Analysis

NASA Astrophysics Data System (ADS)

Earl, Nicholas Michael; STScI

2016-06-01

The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight-forward, consistent way. Through the development of such tools, STScI hopes to unify astronomical data analysis software for JWST and other instruments, allowing for efficient, reliable, and consistent scientific results.

Mars analog minerals' spectral reflectance characteristics under Martian surface conditions

NASA Astrophysics Data System (ADS)

Poitras, J. T.; Cloutis, E. A.; Salvatore, M. R.; Mertzman, S. A.; Applin, D. M.; Mann, P.

2018-05-01

We investigated the spectral reflectance properties of minerals under a simulated Martian environment. Twenty-eight different hydrated or hydroxylated phases of carbonates, sulfates, and silica minerals were selected based on past detection on Mars through spectral remote sensing data. Samples were ground and dry sieved to <45 μm grain size and characterized by XRD before and after 133 days inside a simulated Martian surface environment (pressure 5 Torr and CO2 fed). Reflectance spectra from 0.35 to 4 μm were taken periodically through a sapphire (0.35-2.5 μm) and zinc selenide (2.5-4 μm) window over a 133-day period. Mineral stability on the Martian surface was assessed through changes in spectral characteristics. Results indicate that the hydrated carbonates studied would be stable on the surface of Mars, only losing adsorbed H2O while maintaining their diagnostic spectral features. Sulfates were less stable, often with shifts in the band position of the SO, Fe, and OH absorption features. Silicas displayed spectral shifts related to SiOH and hydration state of the mineral surface, while diagnostic bands for quartz were stable. Previous detection of carbonate minerals based on 2.3-2.5 μm and 3.4-3.9 μm features appears to be consistent with our results. Sulfate mineral detection is more questionable since there can be shifts in band position related to SO4. The loss of the 0.43 μm Fe3+ band in many of the sulfates indicate that there are fewer potential candidates for Fe3+ sulfates to permanently exist on the Martian surface based on this band. The gypsum sample changed phase to basanite during desiccation as demonstrated by both reflectance and XRD. Silica on Mars has been detected using band depth ratio at 1.91 and 1.96 μm and band minimum position of the 1.4 μm feature, and the properties are also used to determine their age. This technique continues to be useful for positive silica identifications, however, silica age appears to be less consistent with our laboratory data. These results will be useful in spectral libraries for characterizing Martian remote sensed data.

3-µm Spectroscopy of Asteroid 16 Psyche

NASA Astrophysics Data System (ADS)

Takir, Driss; Reddy, Vishnu; Sanchez, Juan; Shepard, Michael K.

2016-10-01

Asteroid 16 Psyche, an M-type asteroid, is thought to be one of the most massive exposed iron metal object in the asteroid belt. The high radar albedos of Psyche suggest that this differentiated asteroid is dominantly composed of metal. Psyche was previously found to be featureless in the 3-µm spectral region. However, in our study we found that this asteroid exhibits a 3-µm absorption feature, possibly indicating the presence of hydrated silicates.We have observed Psyche in the 3-µm spectral region, using the long-wavelength cross-dispersed (LXD:1.9-4.2 µm) mode of the SpeX spectrograph/imager at the NASA Infrared Telescope Facility (IRTF). For data reduction, we used the IDL (Interactive Data Language)-based spectral reduction tool Spextool (v4.1). Psyche was observed over the course of three nights with an apparent visual magnitude of ~9.50: 8 December 2015 (3 sets), 9 December 2015 (1 set), and 10 March 2016 (1 set). These observations have revealed that Psyche may exhibit a 3-µm absorption feature, similar to the sharp group in the 2.9-3.3-µm spectral range. Psyche also exhibits an absorption feature similar to the one in Ceres and Ceres-like group in the spectral 3.3-4.0-µm range. These 3-µm observational results revealed that Psyche may not be as featureless as once thought in the 3-µm spectral region.Evidence for the 3-µm band was found on the surfaces of many M-type asteroids and a number of plausible alternative interpretations for the presence of this 3-µm band were previously suggested. These interpretations include the presence of anhydrous silicates containing structural OH, the presence of fluid inclusions, the presence of xenolithic hydrous meteorite components on asteroid surfaces from impacts, solar wind-implanted H, or the presence of troilite. The detection of the Ceres-like feature in the 3.3-4.0-µm spectral range, however, would rule out some of these alternative interpretations, especially the solar wind-implanted H.

Advanced Supersonic Nozzle Concepts: Experimental Flow Visualization Results Paired With LES

NASA Astrophysics Data System (ADS)

Berry, Matthew; Magstadt, Andrew; Stack, Cory; Gaitonde, Datta; Glauser, Mark; Syracuse University Team; The Ohio State University Team

2015-11-01

Advanced supersonic nozzle concepts are currently under investigation, utilizing multiple bypass streams and airframe integration to bolster performance and efficiency. This work focuses on the parametric study of a supersonic, multi-stream jet with aft deck. The single plane of symmetry, rectangular nozzle, displays very complex and unique flow characteristics. Flow visualization techniques in the form of PIV and schlieren capture flow features at various deck lengths and Mach numbers. LES is compared to the experimental results to both validate the computational model and identify limitations of the simulation. By comparing experimental results to LES, this study will help create a foundation of knowledge for advanced nozzle designs in future aircraft. SBIR Phase II with Spectral Energies, LLC under direction of Barry Kiel.

Atom-field dressed states in slow-light waveguide QED

NASA Astrophysics Data System (ADS)

Calajó, Giuseppe; Ciccarello, Francesco; Chang, Darrick; Rabl, Peter

2016-03-01

We discuss the properties of atom-photon bound states in waveguide QED systems consisting of single or multiple atoms coupled strongly to a finite-bandwidth photonic channel. Such bound states are formed by an atom and a localized photonic excitation and represent the continuum analog of the familiar dressed states in single-mode cavity QED. Here we present a detailed analysis of the linear and nonlinear spectral features associated with single- and multiphoton dressed states and show how the formation of bound states affects the waveguide-mediated dipole-dipole interactions between separated atoms. Our results provide both a qualitative and quantitative description of the essential strong-coupling processes in waveguide QED systems, which are currently being developed in the optical and microwave regimes.

Recent Observations and Modeling of Narrowband Stimulated Electromagnetic Emissions SEEs at HAARP and EISCAT

NASA Astrophysics Data System (ADS)

Scales, W.; Mahmoudian, A.; Fu, H.; Bordikar, M. R.; Samimi, A.; Bernhardt, P. A.; Briczinski, S. J., Jr.; Kosch, M. J.; Senior, A.; Isham, B.

2014-12-01

There has been significant interest in so-called narrowband Stimulated Electromagnetic Emission SEE over the past several years due to recent discoveries at the High Frequency Active Auroral Research Program HAARP facility near Gakone, Alaska. Narrowband SEE (NSEE) has been defined as spectral features in the SEE spectrum typically within 1 kHz of the transmitter (or pump) frequency. SEE is due to nonlinear processes leading to re-radiation at frequencies other than the pump wave frequency during heating the ionospheric plasma with high power HF radio waves. Although NSEE exhibits a richly complex structure, it has now been shown after a substantial number of observations at HAARP, that NSEE can be grouped into two basic classes. The first are those spectral features, associated with Stimulated Brillouin Scatter SBS, which typically occur when the pump frequency is not close to electron gyro-harmonic frequencies. Typically, these spectral features are within roughly 50 Hz of the pump wave frequency where it is to be noted that the O+ ion gyro-frequency is roughly 50 Hz. The second class of spectral features corresponds to the case when the pump wave frequency is typically within roughly 10 kHz of electron gyro-harmonic frequencies. In this case, spectral features ordered by harmonics of ion gyro-frequencies are typically observed, and termed Stimulated Ion Bernstein Scatter SIBS. This presentation will first provide an overview of the recent NSEE experimental observations at HAARP. Both Stimulated Brillouin Scatter SBS and Stimulated Ion Bernstein Scatter SIBS observations will be discussed as well as their relationship to each other. Possible theoretical formulation in terms of parametric decay instabilities and computational modeling will be provided. Possible applications of NSEE will be pointed out including triggering diagnostics for artificial ionization layer formation, proton precipitation event diagnostics, electron temperature measurements in the heated volume and detection of heavy ion species. Finally potential for observing such SEE at the European Incoherent Scatter EISCAT facility will be discussed.

Dimensionality-varied convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Liu, Wanjun; Liang, Xuejian; Qu, Haicheng

2017-11-01

Hyperspectral image (HSI) classification is one of the most popular topics in remote sensing community. Traditional and deep learning-based classification methods were proposed constantly in recent years. In order to improve the classification accuracy and robustness, a dimensionality-varied convolutional neural network (DVCNN) was proposed in this paper. DVCNN was a novel deep architecture based on convolutional neural network (CNN). The input of DVCNN was a set of 3D patches selected from HSI which contained spectral-spatial joint information. In the following feature extraction process, each patch was transformed into some different 1D vectors by 3D convolution kernels, which were able to extract features from spectral-spatial data. The rest of DVCNN was about the same as general CNN and processed 2D matrix which was constituted by by all 1D data. So that the DVCNN could not only extract more accurate and rich features than CNN, but also fused spectral-spatial information to improve classification accuracy. Moreover, the robustness of network on water-absorption bands was enhanced in the process of spectral-spatial fusion by 3D convolution, and the calculation was simplified by dimensionality varied convolution. Experiments were performed on both Indian Pines and Pavia University scene datasets, and the results showed that the classification accuracy of DVCNN improved by 32.87% on Indian Pines and 19.63% on Pavia University scene than spectral-only CNN. The maximum accuracy improvement of DVCNN achievement was 13.72% compared with other state-of-the-art HSI classification methods, and the robustness of DVCNN on water-absorption bands noise was demonstrated.

Multi-timescale data assimilation for atmosphere–ocean state estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steiger, Nathan; Hakim, Gregory

2016-06-24

Paleoclimate proxy data span seasonal to millennial timescales, and Earth's climate system has both high- and low-frequency components. Yet it is currently unclear how best to incorporate multiple timescales of proxy data into a single reconstruction framework and to also capture both high- and low-frequency components of reconstructed variables. Here we present a data assimilation approach that can explicitly incorporate proxy data at arbitrary timescales. The principal advantage of using such an approach is that it allows much more proxy data to inform a climate reconstruction, though there can be additional benefits. Through a series of offline data-assimilation-based pseudoproxy experiments,more » we find that atmosphere–ocean states are most skillfully reconstructed by incorporating proxies across multiple timescales compared to using proxies at short (annual) or long (~ decadal) timescales alone. Additionally, reconstructions that incorporate long-timescale pseudoproxies improve the low-frequency components of the reconstructions relative to using only high-resolution pseudoproxies. We argue that this is because time averaging high-resolution observations improves their covariance relationship with the slowly varying components of the coupled-climate system, which the data assimilation algorithm can exploit. These results are consistent across the climate models considered, despite the model variables having very different spectral characteristics. Furthermore, our results also suggest that it may be possible to reconstruct features of the oceanic meridional overturning circulation based on atmospheric surface temperature proxies, though here we find such reconstructions lack spectral power over a broad range of frequencies.« less

Ion nose spectral structures observed by the Van Allen Probes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferradas, C. P.; Zhang, J. -C.; Spence, H. E.

Here, we present a statistical study of nose-like structures observed in energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet. Nose structures are spectral features named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. Using 22 months of observations from the Helium Oxygen Proton Electron (HOPE) instrument onboard Van Allen Probe A, we determine the number of noses observed, and the minimum L-shell reached and energy of each nose on each pass through the inner magnetosphere. We find that multiple noses occur more frequentlymore » in heavy ions than in H +, and are most often observed during quiet times. The heavy-ion noses penetrate to lower L shells than H + noses and there is an energy-magnetic local time (MLT) dependence in the nose locations and energies that is similar for all species. The observations are interpreted using a steady-state model of ion drift in the inner magnetosphere. The model is able to explain the energy and MLT dependence of the different types of nose structures. Different ion charge exchange lifetimes are the main cause for the deeper penetration of heavy-ion noses. The species dependence and preferred geomagnetic conditions of multiple-nose events indicate that they must be on long drift paths, leading to strong charge-exchange effects. The results provide important insight into the spatial distribution, species dependence, and geomagnetic conditions under which nose structures occur.« less

Ion nose spectral structures observed by the Van Allen Probes

DOE PAGES

Ferradas, C. P.; Zhang, J. -C.; Spence, H. E.; ...

2016-11-22

Here, we present a statistical study of nose-like structures observed in energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet. Nose structures are spectral features named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. Using 22 months of observations from the Helium Oxygen Proton Electron (HOPE) instrument onboard Van Allen Probe A, we determine the number of noses observed, and the minimum L-shell reached and energy of each nose on each pass through the inner magnetosphere. We find that multiple noses occur more frequentlymore » in heavy ions than in H +, and are most often observed during quiet times. The heavy-ion noses penetrate to lower L shells than H + noses and there is an energy-magnetic local time (MLT) dependence in the nose locations and energies that is similar for all species. The observations are interpreted using a steady-state model of ion drift in the inner magnetosphere. The model is able to explain the energy and MLT dependence of the different types of nose structures. Different ion charge exchange lifetimes are the main cause for the deeper penetration of heavy-ion noses. The species dependence and preferred geomagnetic conditions of multiple-nose events indicate that they must be on long drift paths, leading to strong charge-exchange effects. The results provide important insight into the spatial distribution, species dependence, and geomagnetic conditions under which nose structures occur.« less

Ion nose spectral structures observed by the Van Allen Probes

NASA Astrophysics Data System (ADS)

Ferradas, C. P.; Zhang, J.-C.; Spence, H. E.; Kistler, L. M.; Larsen, B. A.; Reeves, G.; Skoug, R.; Funsten, H.

2016-12-01

We present a statistical study of nose-like structures observed in energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet. Nose structures are spectral features named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. Using 22 months of observations from the Helium Oxygen Proton Electron instrument onboard Van Allen Probe A, we determine the number of noses observed, and the minimum L shell reached and energy of each nose on each pass through the inner magnetosphere. We find that multiple noses occur more frequently in heavy ions than in H+ and are most often observed during quiet times. The heavy-ion noses penetrate to lower L shells than H+ noses, and there is an energy-magnetic local time (MLT) dependence in the nose locations and energies that is similar for all species. The observations are interpreted by using a steady state model of ion drift in the inner magnetosphere. The model is able to explain the energy and MLT dependence of the different types of nose structures. Different ion charge-exchange lifetimes are the main cause for the deeper penetration of heavy-ion noses. The species dependence and preferred geomagnetic conditions of multiple-nose events indicate that they must be on long drift paths, leading to strong charge-exchange effects. The results provide important insight into the spatial distribution, species dependence, and geomagnetic conditions under which nose structures occur.

Extraction of global 21-cm signal from simulated data for the Dark Ages Radio Explorer (DARE) using an MCMC pipeline

NASA Astrophysics Data System (ADS)

Tauscher, Keith A.; Burns, Jack O.; Rapetti, David; Mirocha, Jordan; Monsalve, Raul A.

2017-01-01

The Dark Ages Radio Explorer (DARE) is a mission concept proposed to NASA in which a crossed dipole antenna collects low frequency (40-120 MHz) radio measurements above the farside of the Moon to detect and characterize the global 21-cm signal from the early (z~35-11) Universe's neutral hydrogen. Simulated data for DARE includes: 1) the global signal modeled using the ares code, 2) spectrally smooth Galactic foregrounds with spatial structure taken from multiple radio foreground maps averaged over a large, well characterized beam, 3) systematics introduced in the data by antenna/receiver reflections, and 4) the Moon. This simulated data is fed into a signal extraction pipeline. As the signal is 4-5 orders of magnitude below the Galactic synchrotron contribution, it is best extracted from the data using Bayesian techniques which take full advantage of prior knowledge of the instrument and foregrounds. For the DARE pipeline, we use the affine-invariant MCMC algorithm implemented in the Python package, emcee. The pipeline also employs singular value decomposition to use known spectral features of the antenna and receiver to form a natural basis with which to fit instrumental systematics. Taking advantage of high-fidelity measurements of the antenna beam (to ~20 ppm) and precise calibration of the instrument, the pipeline extracts the global 21-cm signal with an average RMS error of 10-15 mK for multiple signal models.

An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.

PubMed

Kumar, Shiu; Sharma, Alok; Tsunoda, Tatsuhiko

2017-12-28

Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7-30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine. The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets. Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.

Comparison of two feature selection methods for the separability analysis of intertidal sediments with spectrometric datasets in the German Wadden Sea

NASA Astrophysics Data System (ADS)

Jung, Richard; Ehlers, Manfred

2016-10-01

The spectral features of intertidal sediments are all influenced by the same biophysical properties, such as water, salinity, grain size or vegetation and therefore they are hard to separate by using only multispectral sensors. This could be shown by a previous study of Jung et al. (2015). A more detailed analysis of their characteristic spectral feature has to be carried out to understand the differences and similarities. Spectrometry data (i.e., hyperspectral sensors), for instance, have the opportunity to measure the reflection of the landscape as a continuous spectral pattern for each pixel of an image built from dozen to hundreds of narrow spectral bands. This reveals a high potential to measure unique spectral responses of different ecological conditions (Hennig et al., 2007). In this context, this study uses spectrometric datasets to distinguish between 14 different sediment classes obtained from a study area in the German Wadden Sea. A new feature selection method is proposed (Jeffries-Matusita distance bases feature selection; JMDFS), which uses the Euclidean distance to eliminate the wavelengths with the most similar reflectance values in an iterative process. Subsequent to each iteration, the separation capability is estimated by the Jeffries-Matusita distance (JMD). Two classes can be separated if the JMD is greater than 1.9 and if less than four wavelengths remain, no separation can be assumed. The results of the JMDFS are compared with a state-of-the-art feature selection method called ReliefF. Both methods showed the ability to improve the separation by achieving overall accuracies greater than 82%. The accuracies are 4%-13% better than the results with all wavelengths applied. The number of remaining wavelengths is very diverse and ranges from 14 to 213 of 703. The advantage of JMDFS compared with ReliefF is clearly the processing time. ReliefF needs 30 min for one temporary result. It is necessary to repeat the process several times and to average all temporary results to achieve a final result. In this study 50 iterations were carried out, which makes four days of processing. In contrast, JMDFS needs only 30 min for a final result.

Distribution of hydrothermally altered rocks in the Reko Diq, Pakistan mineralized area based on spectral analysis of ASTER data

USGS Publications Warehouse

Rowan, L.C.; Schmidt, R.G.; Mars, J.C.

2006-01-01

The Reko Diq, Pakistan mineralized study area, approximately 10??km in diameter, is underlain by a central zone of hydrothermally altered rocks associated with Cu-Au mineralization. The surrounding country rocks are a variable mixture of unaltered volcanic rocks, fluvial deposits, and eolian quartz sand. Analysis of 15-band Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data of the study area, aided by laboratory spectral reflectance and spectral emittance measurements of field samples, shows that phyllically altered rocks are laterally extensive, and contain localized areas of argillically altered rocks. In the visible through shortwave-infrared (VNIR + SWIR) phyllically altered rocks are characterized by Al-OH absorption in ASTER band 6 because of molecular vibrations in muscovite, whereas argillically altered rocks have an absorption feature in band 5 resulting from alunite. Propylitically altered rocks form a peripheral zone and are present in scattered exposures within the main altered area. Chlorite and muscovite cause distinctive absorption features at 2.33 and 2.20????m, respectively, although less intense 2.33????m absorption is also present in image spectra of country rocks. Important complementary lithologic information was derived by analysis of the spectral emittance data in the 5 thermal-infrared (TIR) bands. Silicified rocks were not distinguished in the 9 VNIR + SWIR bands because of the lack of diagnostic spectral absorption features in quartz in this wavelength region. Quartz-bearing surficial deposits, as well as hydrothermally silicified rocks, were mapped in the TIR bands by using a band 13/band 12 ratio image, which is sensitive to the intensity of the quartz reststrahlen feature. Improved distinction between the quartzose surficial deposits and silicified bedrock was achieved by using matched-filter processing with TIR image spectra for reference. ?? 2006 Elsevier Inc. All rights reserved.

Ultraviolet spectral reflectance of carbonaceous materials

NASA Astrophysics Data System (ADS)

Applin, Daniel M.; Izawa, Matthew R. M.; Cloutis, Edward A.; Gillis-Davis, Jeffrey J.; Pitman, Karly M.; Roush, Ted L.; Hendrix, Amanda R.; Lucey, Paul G.

2018-06-01

A number of planetary spacecraft missions have carried instruments with sensors covering the ultraviolet (UV) wavelength range. However, there exists a general lack of relevant UV reflectance laboratory data to compare against these planetary surface remote sensing observations in order to make confident material identifications. To address this need, we have systematically analyzed reflectance spectra of carbonaceous materials in the 200-500 nm spectral range, and found spectral-compositional-structural relationships that suggest this wavelength region could distinguish between otherwise difficult-to-identify carbon phases. In particular (and by analogy with the infrared spectral region), large changes over short wavelength intervals in the refractive indices associated with the trigonal sp2π-π* transition of carbon can lead to Fresnel peaks and Christiansen-like features in reflectance. Previous studies extending to shorter wavelengths also show that anomalous dispersion caused by the σ-σ* transition associated with both the trigonal sp2 and tetrahedral sp3 sites causes these features below λ = 200 nm. The peak wavelength positions and shapes of π-π* and σ-σ* features contain information on sp3/sp2, structure, crystallinity, and powder grain size. A brief comparison with existing observational data indicates that the carbon fraction of the surface of Mercury is likely amorphous and submicroscopic, as is that on the surface of the martian satellites Phobos and Deimos, and possibly comet 67P/Churyumov-Gerasimenko, while further coordinated observations and laboratory experiments should refine these feature assignments and compositional hypotheses. The new laboratory diffuse reflectance data reported here provide an important new resource for interpreting UV reflectance measurements from planetary surfaces throughout the solar system, and confirm that the UV can be rich in important spectral information.

THE SPITZER ATLAS OF STELLAR SPECTRA (SASS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech

2010-12-15

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 {mu}m; R {approx} 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, themore » spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.« less

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech; Stauffer, John; Song, Inseok; Rho, Jeonghee; Fajardo-Acosta, Sergio; Hoard, D. W.; Wachter, Stefanie

2010-12-01

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 μm R ~ 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

CCD reflectance spectra of selected asteroids. I - Presentation and data analysis considerations

NASA Technical Reports Server (NTRS)

Vilas, Faith; Mcfadden, Lucy A.

1992-01-01

Narrowband reflectance spectra have been acquired which contribute to the library of asteroid data in the visible and near-IR spectral regions. The spectra support the existence of aqueous alteration products on asteroids located in the outer part of the main asteroid belt out to at least 4 AU. No evidence for features similar to the spectral features of ordinary chondrite meteorites was found in the spectra of asteroids located near the 3:1 Kirkwood Gap chaotic zone.

Evaluation and Improvement of Spectral Features for the Detection of Buried Explosive Hazards Using Forward-Looking Ground-Penetrating Radar

DTIC Science & Technology

2012-07-01

cross track direction is calculated. This is accomplished by taking a 101 point horizontal slice of pixels centered on the alarm. Then, a 101 point...Hamming window, is the 101 -length row vector of FLGPR image pixels surrounding alarm A. We then store the first 50 frequency values (excluding the...Figure 3. Illustration of spectral features in the cross track direction and the difference between actual targets and FAs. Eleven rows of 101

Thermal infrared spectral character of Hawaiian basaltic glasses

NASA Technical Reports Server (NTRS)

Crisp, Joy; Kahle, Anne B.; Abbott, Elsa A.

1990-01-01

Thermal IR reflectance spectra of exposed surfaces of Hawaiian basalt samples from Mauna Loa and Kilauea show systematic changes with age. Spectra of fresh glass collected from active lava flows showed evidence of a strong degree of disorder. After a few weeks of exposure to the laboratory environment, spectra of the top surfaces of these samples began to exhibit spectral features suggestive of ordering into silicate chainlike ansd sheetlike units. With progressive aging, features of apparent sheetlike structures became the preferred mode.

Novel Spectral Representations and Sparsity-Driven Algorithms for Shape Modeling and Analysis

NASA Astrophysics Data System (ADS)

Zhong, Ming

In this dissertation, we focus on extending classical spectral shape analysis by incorporating spectral graph wavelets and sparsity-seeking algorithms. Defined with the graph Laplacian eigenbasis, the spectral graph wavelets are localized both in the vertex domain and graph spectral domain, and thus are very effective in describing local geometry. With a rich dictionary of elementary vectors and forcing certain sparsity constraints, a real life signal can often be well approximated by a very sparse coefficient representation. The many successful applications of sparse signal representation in computer vision and image processing inspire us to explore the idea of employing sparse modeling techniques with dictionary of spectral basis to solve various shape modeling problems. Conventional spectral mesh compression uses the eigenfunctions of mesh Laplacian as shape bases, which are highly inefficient in representing local geometry. To ameliorate, we advocate an innovative approach to 3D mesh compression using spectral graph wavelets as dictionary to encode mesh geometry. The spectral graph wavelets are locally defined at individual vertices and can better capture local shape information than Laplacian eigenbasis. The multi-scale SGWs form a redundant dictionary as shape basis, so we formulate the compression of 3D shape as a sparse approximation problem that can be readily handled by greedy pursuit algorithms. Surface inpainting refers to the completion or recovery of missing shape geometry based on the shape information that is currently available. We devise a new surface inpainting algorithm founded upon the theory and techniques of sparse signal recovery. Instead of estimating the missing geometry directly, our novel method is to find this low-dimensional representation which describes the entire original shape. More specifically, we find that, for many shapes, the vertex coordinate function can be well approximated by a very sparse coefficient representation with respect to the dictionary comprising its Laplacian eigenbasis, and it is then possible to recover this sparse representation from partial measurements of the original shape. Taking advantage of the sparsity cue, we advocate a novel variational approach for surface inpainting, integrating data fidelity constraints on the shape domain with coefficient sparsity constraints on the transformed domain. Because of the powerful properties of Laplacian eigenbasis, the inpainting results of our method tend to be globally coherent with the remaining shape. Informative and discriminative feature descriptors are vital in qualitative and quantitative shape analysis for a large variety of graphics applications. We advocate novel strategies to define generalized, user-specified features on shapes. Our new region descriptors are primarily built upon the coefficients of spectral graph wavelets that are both multi-scale and multi-level in nature, consisting of both local and global information. Based on our novel spectral feature descriptor, we developed a user-specified feature detection framework and a tensor-based shape matching algorithm. Through various experiments, we demonstrate the competitive performance of our proposed methods and the great potential of spectral basis and sparsity-driven methods for shape modeling.

Extracting the frequencies of the pinna spectral notches in measured head related impulse responses

NASA Astrophysics Data System (ADS)

Raykar, Vikas C.; Duraiswami, Ramani; Yegnanarayana, B.

2005-07-01

The head related impulse response (HRIR) characterizes the auditory cues created by scattering of sound off a person's anatomy. The experimentally measured HRIR depends on several factors such as reflections from body parts (torso, shoulder, and knees), head diffraction, and reflection/diffraction effects due to the pinna. Structural models (Algazi et al., 2002; Brown and Duda, 1998) seek to establish direct relationships between the features in the HRIR and the anatomy. While there is evidence that particular features in the HRIR can be explained by anthropometry, the creation of such models from experimental data is hampered by the fact that the extraction of the features in the HRIR is not automatic. One of the prominent features observed in the HRIR, and one that has been shown to be important for elevation perception, are the deep spectral notches attributed to the pinna. In this paper we propose a method to robustly extract the frequencies of the pinna spectral notches from the measured HRIR, distinguishing them from other confounding features. The method also extracts the resonances described by Shaw (1997). The techniques are applied to the publicly available CIPIC HRIR database (Algazi et al., 2001c). The extracted notch frequencies are related to the physical dimensions and shape of the pinna.

A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

THE VIEWING ANGLES OF BROAD ABSORPTION LINE VERSUS UNABSORBED QUASARS

DOE Office of Scientific and Technical Information (OSTI.GOV)

DiPompeo, M. A.; Brotherton, M. S.; De Breuck, C.

2012-06-10

It was recently shown that there is a significant difference in the radio spectral index distributions of broad absorption line (BAL) quasars and unabsorbed quasars, with an overabundance of BAL quasars with steeper radio spectra. This result suggests that source orientation does play into the presence or absence of BAL features. In this paper, we provide more quantitative analysis of this result based on Monte Carlo simulations. While the relationship between viewing angle and spectral index does indeed contain a lot of scatter, the spectral index distributions are different enough to overcome that intrinsic variation. Utilizing two different models ofmore » the relationship between spectral index and viewing angle, the simulations indicate that the difference in spectral index distributions can be explained by allowing BAL quasar viewing angles to extend about 10 Degree-Sign farther from the radio jet axis than non-BAL sources, though both can be seen at small angles. These results show that orientation cannot be the only factor determining whether BAL features are present, but it does play a role.« less