EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

PubMed

Kortelainen, Jukka; Seppänen, Tapio

2013-01-01

Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.

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.

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.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

Attenuated total reflectance spectroscopy of plant leaves: A tool for ecological and botanical studies

USGS Publications Warehouse

Ribeiro da Luz, B.

2006-01-01

??? Attenuated total reflectance (ATR) spectra of plant leaves display complex absorption features related to organic constituents of leaf surfaces. The spectra can be recorded rapidly, both in the field and in the laboratory, without special sample preparation. ??? This paper explores sources of ATR spectral variation in leaves, including compositional, positional and temporal variations. Interspecific variations are also examined, including the use of ATR spectra as a tool for species identification. ??? Positional spectral variations generally reflected the abundance of cutin and the epicuticular wax thickness and composition. For example, leaves exposed to full sunlight commonly showed more prominent cutin- and wax-related absorption features compared with shaded leaves. Adaxial vs. abaxial leaf surfaces displayed spectral variations reflecting differences in trichome abundance and wax composition. Mature vs. young leaves showed changes in absorption band position and intensity related to cutin, polysaccharide, and possibly amorphous silica development on and near the leaf surfaces. ??? Provided that similar samples are compared (e.g. adaxial surfaces of mature, sun-exposed leaves) same-species individuals display practically identical ATR spectra. Using spectral matching procedures to analyze an ATR database containing 117 individuals, including 32 different tree species, 83% of the individuals were correctly identified. ?? The Authors (2006).

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.

Visible and near-IR spectral reflectance of geologically important materials: A short review

NASA Technical Reports Server (NTRS)

Singer, R. B.

1982-01-01

Examples of reflectance spectra are presented and discussed for various mineral groups including pyroxenes, olivene, phylosilicates, amphiboles, feldspars, oxides and hydroxides, carbonates, and mixtures of minerals. The physical sources of some spectral features are also reviewed such as charge transfer and conduction bands, crystal field absorptions, and vibrational absorptions.

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.

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.

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.

Linking Spectral Features with Composition, Crystallinity, and Roughness Properties of Silica and Implications for Candidate Hydrothermal Systems on Mars

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; McDowell, M. L.; Berger, J. A.; Cady, S. L.; Knauth, L. P.

2011-12-01

We have collected visible to near infrared reflectance (VNIR, ~0.4 - 2.5 um), thermal infrared emissivity (TIR, ~5 - 45 um), SEM, XRD, surface roughness, and petrographic data for 18 silica samples. These rocks (e.g., replacement chert, geyserite, opal-A/-CT) represent a variety of geologic formation environments, including hydrothermal, and have XRD-determined crystallinities ranging from <1 to >10 according to the quartz crystallinity index. Our findings are relevant to the interpretation of orbital and in situ spectral observations of crystalline or amorphous silica on the Martian surface, some of which may have formed in hydrothermal systems. Almost all of our samples' VNIR spectra contain discernible bands. The most common features are related to hydration (H2O and/or OH) of silica (e.g., at ~1.4, 1.9, and 2.2 um). The visibility and strength of these bands is not always constant between spectra from different areas of a sample. Other features include those of carbonate, phyllosilicate, and iron oxide impurities. All of our amorphous silica samples have hydration features in the VNIR, but we note that the absorptions around ~2.2 um can be very weak in amorphous samples relative to features at other wavelengths and relative to ~2.2-um features observed in Martian data, suggesting that some amorphous silica on Mars could go undetected. Deposits containing significant anhydrous, crystalline silica (chert) may be assumed to lack features in the VNIR, but many of our cherts have spectral features and could be misidentified as materials dominated by what is a minor contaminant. Thermal infrared spectra of chert and opaline silica differ from each other as a result of the loss of long-range Si-O order in increasingly amorphous samples. Our samples display a clear trend in TIR band shapes where features attributable to crystalline quartz and amorphous silica are blended in samples with intermediate crystallinities. Most diagnostic TIR spectral features observable in laboratory data typically are recognizable in hyperspectral remote sensing data. These features are more difficult to distinguish (or are not included) at multispectral resolutions, but in nearly all uncontaminated samples, the positions of Si-O emissivity minima shift towards longer wavelengths with decreasing crystallinity. Contaminating phases with strong VNIR spectral features are observed in some of the TIR spectra but have a negligible effect in others, suggesting that TIR spectroscopy helps constrain the abundances of these phases. In addition to compositional and crystallinity information, our laboratory data demonstrate that TIR spectra can be used to deduce important information on silica phases' texture and orientation. If used in combination, VNIR and TIR spectroscopy can detect and characterize silica phases, allowing us to estimate conditions of silica formation, e.g., high- or low-temperature aqueous systems.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

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

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

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.

[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.

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.

Application of musical timbre discrimination features to active sonar classification

NASA Astrophysics Data System (ADS)

Young, Victor W.; Hines, Paul C.; Pecknold, Sean

2005-04-01

In musical acoustics significant effort has been devoted to uncovering the physical basis of timbre perception. Most investigations into timbre rely on multidimensional scaling (MDS), in which different musical sounds are arranged as points in multidimensional space. The Euclidean distance between points corresponds to the perceptual distance between sounds and the multidimensional axes are linked to measurable properties of the sounds. MDS has identified numerous temporal and spectral features believed to be important to timbre perception. There is reason to believe that some of these features may have wider application in the disparate field of underwater acoustics, since anecdotal evidence suggests active sonar returns from metallic objects sound different than natural clutter returns when auralized by human operators. This is particularly encouraging since attempts to develop robust automatic classifiers capable of target-clutter discrimination over a wide range of operational conditions have met with limited success. Spectral features relevant to target-clutter discrimination are believed to include click-pitch and envelope irregularity; relevant temporal features are believed to include duration, sub-band attack/decay time, and time separation pitch. Preliminary results from an investigation into the role of these timbre features in target-clutter discrimination will be presented. [Work supported by NSERC and GDC.

Pulse shaping in mode-locked fiber lasers by in-cavity spectral filter.

PubMed

Boscolo, Sonia; Finot, Christophe; Karakuzu, Huseyin; Petropoulos, Periklis

2014-02-01

We numerically show the possibility of pulse shaping in a passively mode-locked fiber laser by inclusion of a spectral filter into the laser cavity. Depending on the amplitude transfer function of the filter, we are able to achieve various regimes of advanced temporal waveform generation, including ones featuring bright and dark parabolic-, flat-top-, triangular- and saw-tooth-profiled pulses. The results demonstrate the strong potential of an in-cavity spectral pulse shaper for controlling the dynamics of mode-locked fiber lasers.

Spectral confocal reflection microscopy using a white light source

NASA Astrophysics Data System (ADS)

Booth, M.; Juškaitis, R.; Wilson, T.

2008-08-01

We present a reflection confocal microscope incorporating a white light supercontinuum source and spectral detection. The microscope provides images resolved spatially in three-dimensions, in addition to spectral resolution covering the wavelength range 450-650nm. Images and reflection spectra of artificial and natural specimens are presented, showing features that are not normally revealed in conventional microscopes or confocal microscopes using discrete line lasers. The specimens include thin film structures on semiconductor chips, iridescent structures in Papilio blumei butterfly scales, nacre from abalone shells and opal gemstones. Quantitative size and refractive index measurements of transparent beads are derived from spectral interference bands.

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.

AVIRIS spectra of California wetlands

NASA Technical Reports Server (NTRS)

Gross, Michael F.; Ustin, Susan L.; Klemas, Vytautas

1988-01-01

Spectral data gathered by the AVIRIS from wetlands in the Suisun Bay area of California on 13 October 1987 were analyzed. Spectra representing stands of numerous vegetation types (including Sesuvium verrucosum, Scirpus acutus and Scirpus californicus, Xanthium strumarium, Cynadon dactylon, and Distichlis spicata) and soil were isolated. Despite some defects in the data, it was possible to detect vegetation features such as differences in the location of the chlorophyll red absorption maximum. Also, differences in cover type spectra were evident in other spectral regions. It was not possible to determine if the observed features represent noise, variability in canopy architecture, or chemical constituents of leaves.

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.

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.

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.

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

Recent Observations and Modeling of Narrowband Stimulated Electromagnetic Emissions SEEs at the HAARP Facility

NASA Astrophysics Data System (ADS)

Scales, Wayne; Bernhardt, Paul; McCarrick, Michael; Briczinski, Stanley; Mahmoudian, Alireza; Fu, Haiyang; Ranade Bordikar, Maitrayee; Samimi, Alireza

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. There is also important parametric behavior on both classes of NSEE depending on the pump wave parameters including the field strength, antenna beam angle, and electron gyro-harmonic number. 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 will be provided. Computer simulation model results will be presented to provide insight into associated higher order nonlinear effects including particle acceleration and wave-wave processes. Both theory and model results will be put into the context of the experimental observations. Finally, possible applications of NSEE will be pointed out including triggering diagnostics for artificial ionization layer formation, proton precipitation event diagnostics, and electron temperature measurements in the heated volume.

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound.

PubMed

Oelze, Michael L; Mamou, Jonathan

2016-02-01

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and preclinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

Review of quantitative ultrasound: envelope statistics and backscatter coefficient imaging and contributions to diagnostic ultrasound

PubMed Central

Oelze, Michael L.; Mamou, Jonathan

2017-01-01

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging techniques can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient, estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter and the effective acoustic concentration of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and pre-clinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy. PMID:26761606

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.

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.

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.

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).

Results from the calibration of the Extreme Ultraviolet Explorer instruments

NASA Technical Reports Server (NTRS)

Welsh, Barry Y.; Jelinsky, Pat; Vedder, Peter W.; Vallerga, John V.; Finley, David S.; Malina, Roger F.

1991-01-01

The paper describes the main features and selected results of the calibration of the scientific instruments to be flown on the Extreme Ultraviolet Explorer in 1991. The instrument payload includes three grazing incidence scanning telescopes and an EUV spectrometer/deep survey instrument covering the spectral region 70-800 A. The measured imaging characteristics, the effective areas, and the details of spectral responses of the instruments are presented. Diagrams of the cross-sectional views of the scanning telescope and the deep-survey/spectrometer telescope are included.

Analysis of scanner data for crop inventories

NASA Technical Reports Server (NTRS)

Horvath, R. (Principal Investigator); Cicone, R. C.; Kauth, R. J.; Malila, W. A.; Pont, W.; Thelen, B.; Sellman, A.

1981-01-01

Accomplishments for a machine-oriented small grains labeler T&E, and for Argentina ground data collection are reported. Features of the small grains labeler include temporal-spectral profiles, which characterize continuous patterns of crop spectral development, and crop calendar shift estimation, which adjusts for planting date differences of fields within a crop type. Corn and soybean classification technology development for area estimation for foreign commodity production forecasting is reported. Presentations supporting quarterly project management reviews and a quarterly technical interchange meeting are also included.

Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.

1995-01-01

One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.

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.

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.

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.

Performance evaluation of object based greenhouse detection from Sentinel-2 MSI and Landsat 8 OLI data: A case study from Almería (Spain)

NASA Astrophysics Data System (ADS)

Novelli, Antonio; Aguilar, Manuel A.; Nemmaoui, Abderrahim; Aguilar, Fernando J.; Tarantino, Eufemia

2016-10-01

This paper shows the first comparison between data from Sentinel-2 (S2) Multi Spectral Instrument (MSI) and Landsat 8 (L8) Operational Land Imager (OLI) headed up to greenhouse detection. Two closely related in time scenes, one for each sensor, were classified by using Object Based Image Analysis and Random Forest (RF). The RF input consisted of several object-based features computed from spectral bands and including mean values, spectral indices and textural features. S2 and L8 data comparisons were also extended using a common segmentation dataset extracted form VHR World-View 2 (WV2) imagery to test differences only due to their specific spectral contribution. The best band combinations to perform segmentation were found through a modified version of the Euclidian Distance 2 index. Four different RF classifications schemes were considered achieving 89.1%, 91.3%, 90.9% and 93.4% as the best overall accuracies respectively, evaluated over the whole study area.

M dwarf spectra from 0.6 to 1.5 micron - A spectral sequence, model atmosphere fitting, and the temperature scale

NASA Technical Reports Server (NTRS)

Kirkpatrick, J. D.; Kelly, Douglas M.; Rieke, George H.; Liebert, James; Allard, France; Wehrse, Rainer

1993-01-01

Red/infrared (0.6-1.5 micron) spectra are presented for a sequence of well-studied M dwarfs ranging from M2 through M9. A variety of temperature-sensitive features useful for spectral classification are identified. Using these features, the spectral data are compared to recent theoretical models, from which a temperature scale is assigned. The red portion of the model spectra provide reasonably good fits for dwarfs earlier than M6. For layer types, the infrared region provides a more reliable fit to the observations. In each case, the wavelength region used includes the broad peak of the energy distribution. For a given spectral type, the derived temperature sequence assigns higher temperatures than have earlier studies - the difference becoming more pronounced at lower luminosities. The positions of M dwarfs on the H-R diagram are, as a result, in closer agreement with theoretical tracks of the lower main sequence.

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.

Modelling of celestial backgrounds

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.; Lim, Jae-Wan; Jeon, Yun-Ho

2018-05-01

For applications where a sensor's image includes the celestial background, stars and Solar System Bodies compromise the ability of the sensor system to correctly classify a target. Such false targets are particularly significant for the detection of weak target signatures which only have a small relative angular motion. The detection of celestial features is well established in the visible spectral band. However, given the increasing sensitivity and low noise afforded by emergent infrared focal plane array technology together with larger and more efficient optics, the signatures of celestial features can also impact performance at infrared wavelengths. A methodology has been developed which allows the rapid generation of celestial signatures in any required spectral band using star data from star catalogues and other open-source information. Within this paper, the radiometric calculations are presented to determine the irradiance values of stars and planets in any spectral band.

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.

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.

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.

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.

Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

PubMed Central

Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

2012-01-01

Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps With Manifold Harmonics.

PubMed

Sanroman-Junquera, Margarita; Mora-Jimenez, Inmaculada; Garcia-Alberola, Arcadio; Caamano, Antonio J; Trenor, Beatriz; Rojo-Alvarez, Jose L

2018-04-01

Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR). Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units. With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the "early-meets-late" in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm. The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.

Fluorescence and reflectance properties of hemoglobin-pigmented skin disorders

NASA Astrophysics Data System (ADS)

Troyanova, P.; Borisova, E.; Avramov, L.

2007-06-01

There has been growing interest in clinical application of laser-induced autofluorescence (LIAF) and reflectance spectroscopy (RS) to differentiate disease from normal surrounding tissue, including skin pathologies. Pigmented cutaneous lesions diagnosis plays important role in clinical practice, as malignant melanoma, which is characterized with greatest mortality from all skin cancer types, must be carefully discriminated form other colorized pathologies. The goals of this work were investigation of cutaneous hemoglobin-pigmented lesions (heamangioma, angiokeratoma, and fibroma) by the methods of LIAFS and RS. Spectra from healthy skin areas near to the lesion were detected to be used posteriori in analysis. Fluorescence and reflectance of cutaneous hemoglobin-pigmented lesions are used to develop criterion for differentiation from other pigmented pathologies. Origins of the spectral features obtained are discussed and determination of lesion types is achieved using selected spectral features. The spectral results, obtained were used to develop multispectral diagnostic algorithms based on the most prominent spectral features from the fluorescence and reflectance spectra of the lesions investigated. In comparison between normal skin and different cutaneous lesion types and between lesion types themselves sensitivities and specificities higher than 90 % were achieved. These results show a perspective possibility to differentiate hemoglobin-pigmented lesions from other pigmented pathologies using non-invasive and real time discrimination procedure.

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.

CONNJUR Workflow Builder: A software integration environment for spectral reconstruction

PubMed Central

Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert; Martyn, Timothy O.; Ellis, Heidi J.C.; Gryk, Michael R.

2015-01-01

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses. PMID:26066803

CONNJUR Workflow Builder: a software integration environment for spectral reconstruction.

PubMed

Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert; Martyn, Timothy O; Ellis, Heidi J C; Gryk, Michael R

2015-07-01

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses.

[EEG-correlates of pilots' functional condition in simulated flight dynamics].

PubMed

Kiroy, V N; Aslanyan, E V; Bakhtin, O M; Minyaeva, N R; Lazurenko, D M

2015-01-01

The spectral characteristics of the EEG recorded on two professional pilots in the simulator TU-154 aircraft in flight dynamics, including takeoff, landing and horizontal flight (in particular during difficult conditions) were analyzed. EEG recording was made with frequency band 0.1-70 Hz continuously from 15 electrodes. The EEG recordings were evaluated using analysis of variance and discriminant analysis. Statistical significant of the identified differences and the influence of the main factors and their interactions were evaluated using Greenhouse - Gaiser corrections. It was shown that the spectral characteristics of the EEG are highly informative features of the state of the pilots, reflecting the different flight phases. High validity ofthe differences including individual characteristic, indicates their non-random nature and the possibility of constructing a system of pilots' state control during all phases of flight, based on EEG features.

Hyperspectral Features of Oil-Polluted Sea Ice and the Response to the Contamination Area Fraction

PubMed Central

Li, Ying; Liu, Chengyu; Xie, Feng

2018-01-01

Researchers have studied oil spills in open waters using remote sensors, but few have focused on extracting reflectance features of oil pollution on sea ice. An experiment was conducted on natural sea ice in Bohai Bay, China, to obtain the spectral reflectance of oil-contaminated sea ice. The spectral absorption index (SAI), spectral peak height (SPH), and wavelet detail coefficient (DWT d5) were calculated using stepwise multiple linear regression. The reflectances of some false targets were measured and analysed. The simulated false targets were sediment, iron ore fines, coal dust, and the melt pool. The measured reflectances were resampled using five common sensors (GF-2, Landsat8-OLI, Sentinel3-OLCI, MODIS, and AVIRIS). Some significant spectral features could discriminate between oil-polluted and clean sea ice. The indices correlated well with the oil area fractions. All of the adjusted R2 values exceeded 0.9. The SPH model1, based on spectral features at 507–670 and 1627–1746 nm, displayed the best fitting. The resampled data indicated that these multi-spectral and hyper-spectral sensors could be used to detect crude oil on the sea ice if the effect of noise and spatial resolution are neglected. The spectral features and their identified changes may provide reference on sensor design and band selection. PMID:29342945

Infrared (2.08-14 micron) spectra of powered stony meteorites

NASA Technical Reports Server (NTRS)

Salisbury, J. W.; Daria, D. M.; Jarosewich, E.

1991-01-01

Infrared biconical reflectance spectra of 60 powdered meteorite samples, representing 50 different stony meteorites, were measured as analogues of asteroidal regolith. Representative samples were measured in directional hemispherical reflectance to assure that Kirchhoff's Law can be used to predict relative emissivity from the reflectance spectra. These spectral data confirm that the O-H fundamental absorption band near 2.9 microns is an extremely sensitive indicator of incipient alteration, which often has taken place in powdered meteorite samples exposed only to water vapor in the air. Such non-carbonaceous samples typically contain less than 1 percent water by weight. Likewise, the C-H fundamental absorption bands near 3.4 and 3.5 microns are equally sensitive indicators of contamination with volatile hydrocarbons, which can also be absorbed from the air. The heavy, macromolecular hydrocarbons native to chondrites do not display such heavy bands, making detection of these bands in remote sensing of asteroids unlikely. Despite the spectral artifacts introduced by alteration and hydrocarbon contamination, powdered stony meteorites display a wide variety of real spectral features that can be used for their identification, including residual reststrahlen bands, absorption bands, and the Christiansen feature. Researchers found that the wavelengths of the peaks or troughs of each of these spectral features can be used independently to infer meteorite composition, but the best results are obtained when the entire spectral curve is used, or at least the portion of it encompassed by the 8 to 14 micron atmospheric window, in a digital search library.

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.

Dynamics of short-pulse generation via spectral filtering from intensely excited gain-switched 1.55-μm distributed-feedback laser diodes.

PubMed

Chen, Shaoqiang; Yoshita, Masahiro; Sato, Aya; Ito, Takashi; Akiyama, Hidefumi; Yokoyama, Hiroyuki

2013-05-06

Picosecond-pulse-generation dynamics and pulse-width limiting factors via spectral filtering from intensely pulse-excited gain-switched 1.55-μm distributed-feedback laser diodes were studied. The spectral and temporal characteristics of the spectrally filtered pulses indicated that the short-wavelength component stems from the initial part of the gain-switched main pulse and has a nearly linear down-chirp of 5.2 ps/nm, whereas long-wavelength components include chirped pulse-lasing components and steady-state-lasing components. Rate-equation calculations with a model of linear change in refractive index with carrier density explained the major features of the experimental results. The analysis of the expected pulse widths with optimum spectral widths was also consistent with the experimental data.

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.

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.

WUVS simulator: detectability of spectral lines with the WSO-UV spectrographs

NASA Astrophysics Data System (ADS)

Marcos-Arenal, Pablo; de Castro, Ana I. Gómez; Abarca, Belén Perea; Sachkov, Mikhail

2017-04-01

The World Space Observatory Ultraviolet telescope is equipped with high dispersion (55,000) spectrographs working in the 1150 to 3100 Å spectral range. To evaluate the impact of the design on the scientific objectives of the mission, a simulation software tool has been developed. This simulator builds on the development made for the PLATO space mission and it is designed to generate synthetic time-series of images by including models of all important noise sources. We describe its design and performance. Moreover, its application to the detectability of important spectral features for star formation and exoplanetary research is addressed.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. We present a case study of the temporal evolution of H+, He+, and O+ spectral structures throughout the geomagnetic storm of 2 October 2013. We use data from the Helium, Oxygen, Proton, and Electron (HOPE) mass spectrometer onboard Van Allen Probe A to analyze the spectral structures in the energy range of 1- 50 keV. We find that the characteristics of the ion structures follow a cyclic pattern, the observed features changing dramatically as the storm starts and then returning to its initial pre-storm state. Quiet, pre-storm times are characterized by multiple and often complex flux structures at narrow energy bands. During the storm main phase, the observed features become simple, with no nose structures or only one nose structure present in the energy-time spectrograms. As the inner magnetosphere recovers from the storm, more complex structures appear once again. Additionally, the heavy ion spectral features are generally more complex than the H+ features, with multiple noses being observed more often in the heavy ion spectra. We use a model of ion drift and losses due to charge exchange to understand the formation of the spectral features and their species dependence.

Visualization of Near-Infrared Spectral Data of Eros Using the Small Body Mapping Tool

NASA Astrophysics Data System (ADS)

Klima, Rachel L.; Ernst, Carolyn

2016-10-01

One of the primary drivers for many missions visiting asteroids is to advance our understanding of their composition beyond what can be (and is) already measured by telescopes. Without sample return or lander missions, this task relies primarily on resolved near-infrared spectroscopic measurements. Scientific analysis using spectral data collected by point spectrometers is not as straightforward as for imaging spectrometers, where the local spatial context is immediately available. In the case of Eros and other highly non-spherical bodies, this problem becomes even more severe when trying to locate spectra that cross a mapped feature that bends over an irregularly shaped surface. Thus, it is often the case that outside of the mission teams, few from the community at large delve into these data sets, as they lack the tools necessary to incorporate the spectral information into geological analyses of the asteroids. Ultimately, we seek to make such spectral datasets, which NASA has invested significant amounts of money to obtain, more widely accessible and user-friendly. The Small Bodies Mapping Tool (SBMT) is a Java-based, interactive, three-dimensional visualization tool written and developed at APL to map and analyze features on irregularly shaped solar system bodies. The SBMT can be used to locate and then "drape" spacecraft images, spectra, and laser altimetry around the shape model of such bodies. It provides a means for rapid identification of available data in a region of interest and allows features to be mapped directly onto the shape model. The program allows the free rotation of a shape model (including any overlain data) in all directions, so that the correlation and distribution of mapped features can be easily and globally observed.We will present the results of our work on the NEAR/Near-Infrared Spectrograph (NIS) data, including improvements to the calibration made by using the geometric information provided by the SBMT and improvements to the SMBT itself to allow spectral visualization, manipulation, and analysis of these data in a spatial context.

[Review of digital ground object spectral library].

PubMed

Zhou, Xiao-Hu; Zhou, Ding-Wu

2009-06-01

A higher spectral resolution is the main direction of developing remote sensing technology, and it is quite important to set up the digital ground object reflectance spectral database library, one of fundamental research fields in remote sensing application. Remote sensing application has been increasingly relying on ground object spectral characteristics, and quantitative analysis has been developed to a new stage. The present article summarized and systematically introduced the research status quo and development trend of digital ground object reflectance spectral libraries at home and in the world in recent years. Introducing the spectral libraries has been established, including desertification spectral database library, plants spectral database library, geological spectral database library, soil spectral database library, minerals spectral database library, cloud spectral database library, snow spectral database library, the atmosphere spectral database library, rocks spectral database library, water spectral database library, meteorites spectral database library, moon rock spectral database library, and man-made materials spectral database library, mixture spectral database library, volatile compounds spectral database library, and liquids spectral database library. In the process of establishing spectral database libraries, there have been some problems, such as the lack of uniform national spectral database standard and uniform standards for the ground object features as well as the comparability between different databases. In addition, data sharing mechanism can not be carried out, etc. This article also put forward some suggestions on those problems.

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.

Emotion Recognition from Single-Trial EEG Based on Kernel Fisher's Emotion Pattern and Imbalanced Quasiconformal Kernel Support Vector Machine

PubMed Central

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-01-01

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods. PMID:25061837

Emotion recognition from single-trial EEG based on kernel Fisher's emotion pattern and imbalanced quasiconformal kernel support vector machine.

PubMed

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-07-24

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods.

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.

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.

Theoretical Investigation of Anharmonic Effects Observed in the Infrared Spectra of the Formaldehyde Cation and its Hydroxymethylene Isomer

NASA Astrophysics Data System (ADS)

Madison, Lindsey R.; Mosley, Jonathan; Mauney, Daniel; Duncan, Michael A.; McCoy, Anne B.

2016-06-01

Formaldehyde is the smallest organic molecule and is a prime candidate for a thorough investigation regarding the anharmonic approximations made in computationally modeling its infrared spectrum. Mass-selected ion spectroscopy was used to detect mass 30 cations which include of HCOH^+ and CH_2O^+. In order to elucidate the differences between the structures of these isomers, infrared spectroscopy was performed on the mass 30 cations using Ar predissociation. Interestingly, several additional spectral features are observed that cannot be explained by the fundamental OH and CH stretch vibrations alone. By including anharmonic coupling between OH and CH stretching and various overtones and combination bands involving lower frequency vibrations, we are able to identify how specific modes couple and lead to the experimentally observed spectral features. We combine straight-forward, ab initio calculations of the anharmonic frequencies of the mass 30 cations with higher order, adiabatic approximations and Fermi resonance models. By including anharmonic effects we are able to confirm that the isomers of the CH_2O^+\\cdotAr system have substantially different, and thus distinguishable, IR spectra and that many of the features can only be explained with anharmonic treatments.

The US Geological Survey, digital spectral reflectance library: version 1: 0.2 to 3.0 microns

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.; King, Trude V. V.; Gallagher, Andrea J.; Calvin, Wendy M.

1993-01-01

We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 500 spectra of 447 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 microns. The spectral resolution (Full Width Half Maximum) of the reflectance data is less than or equal to 4 nm in the visible (0.2-0.8 microns) and less than or equal 10 nm in the NIR (0.8-2.35 microns). All spectra were corrected to absolute reflectance using an NBS Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from sulfide, oxide, hydroxide, halide, carbonate, nitrate, borate, phosphate, and silicate groups are represented. X-ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses.

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.

Ultra-Widefield Steering-Based Spectral-Domain Optical Coherence Tomography Imaging of the Retinal Periphery.

PubMed

Choudhry, Netan; Golding, John; Manry, Matthew W; Rao, Rajesh C

2016-06-01

To describe the spectral-domain optical coherence tomography (SD OCT) features of peripheral retinal findings using an ultra-widefield (UWF) steering technique to image the retinal periphery. Observational study. A total of 68 patients (68 eyes) with 19 peripheral retinal features. Spectral-domain OCT-based structural features. Nineteen peripheral retinal features, including vortex vein, congenital hypertrophy of the retinal pigment epithelium, pars plana, ora serrata pearl, typical cystoid degeneration (TCD), cystic retinal tuft, meridional fold, lattice and cobblestone degeneration, retinal hole, retinal tear, rhegmatogenous retinal detachment, typical degenerative senile retinoschisis, peripheral laser coagulation scars, ora tooth, cryopexy scars (retinal tear and treated retinoblastoma scar), bone spicules, white without pressure, and peripheral drusen, were identified by peripheral clinical examination. Near-infrared scanning laser ophthalmoscopy images and SD OCT of these entities were registered to UWF color photographs. Spectral-domain OCT resolved structural features of all peripheral findings. Dilated hyporeflective tubular structures within the choroid were observed in the vortex vein. Loss of retinal lamination, neural retinal attenuation, retinal pigment epithelium loss, or hypertrophy was seen in several entities, including congenital hypertrophy of the retinal pigment epithelium, ora serrata pearl, TCD, cystic retinal tuft, meridional fold, lattice, and cobblestone degenerations. Hyporeflective intraretinal spaces, indicating cystoid or schitic fluid, were seen in ora serrata pearl, ora tooth, TCD, cystic retinal tuft, meridional fold, retinal hole, and typical degenerative senile retinoschisis. The vitreoretinal interface, which often consisted of lamellae-like structures of the condensed cortical vitreous near or adherent to the neural retina, appeared clearly in most peripheral findings, confirming its association with many low-risk and vision-threatening pathologies, such as lattice degeneration, meridional folds, retinal breaks, and rhegmatogenous retinal detachments. Ultra-widefield steering-based SD OCT imaging of the retinal periphery is feasible with current commercially available devices and provides detailed anatomic information of the peripheral retina, including benign and pathologic entities, not previously imaged. This imaging technique may deepen our structural understanding of these entities and their potentially associated macular and systemic pathologies, and may influence decision-making in clinical practice, particularly in areas with teleretinal capabilities but poor access to retinal specialists. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Infrared Space Observatory Observations of Far-Infrared Rotational Emission Lines of Water Vapor Toward the Supergiant Star VY Canis Majoris

NASA Technical Reports Server (NTRS)

Neufeld, David A.; Feuchtgruber, Helmut; Harwit, Martin; Melnick, Gary J.

1999-01-01

We report the detection of numerous far-infrared emission lines of water vapor toward the supergiant star VY Canis Majoris. A 29.5-45 micron grating scan of VY CMa, obtained using the Short-Wavelength Spectrometer (SWS) of the Infrared Space Observatory at a spectral resolving power lambda/delat.lambda of approximately 2000, reveals at least 41 spectral features due to water vapor that together radiate a total luminosity of approximately 25 solar luminosity . In addition to pure rotational transitions within the ground vibrational state, these features include rotational transitions within the (010) excited vibrational state. The spectrum also shows the (sup 2)product(sub 1/2) (J = 5/2) left arrow (sup 2)product(sub 3/2) (J = 3/2) OH feature near 34.6 micron in absorption. Additional SWS observations of VY CMa were carried out in the instrument's Fabry-Perot mode for three water transitions: the 7(sub 25)-6(sub 16) line at 29.8367 micron, the 4(sub 41)-3(sub 12) line at 31.7721 micron, and the 4(sub 32)-3(sub 03) line at 40.6909 micron. The higher spectral resolving power lambda/delta.lambda of approximately 30,000 thereby obtained permits the line profiles to be resolved spectrally for the first time and reveals the "P Cygni" profiles that are characteristic of emission from an outflowing envelope.

Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Wang, Yanchun; Liu, Wu

2017-11-01

This paper proposes a novel classification paradigm for hyperspectral image (HSI) using feature-level fusion and deep learning-based methodologies. Operation is carried out in three main steps. First, during a pre-processing stage, wave atoms are introduced into bilateral filter to smooth HSI, and this strategy can effectively attenuate noise and restore texture information. Meanwhile, high quality spectral-spatial features can be extracted from HSI by taking geometric closeness and photometric similarity among pixels into consideration simultaneously. Second, higher order statistics techniques are firstly introduced into hyperspectral data classification to characterize the phase correlations of spectral curves. Third, multifractal spectrum features are extracted to characterize the singularities and self-similarities of spectra shapes. To this end, a feature-level fusion is applied to the extracted spectral-spatial features along with higher order statistics and multifractal spectrum features. Finally, stacked sparse autoencoder is utilized to learn more abstract and invariant high-level features from the multiple feature sets, and then random forest classifier is employed to perform supervised fine-tuning and classification. Experimental results on two real hyperspectral data sets demonstrate that the proposed method outperforms some traditional alternatives.

Spectral reflectance properties (0.4-2.5 μm) of secondary Fe-oxide, Fe-hydroxide, and Fe-sulphate-hydrate minerals associated with sulphide-bearing mine wastes

USGS Publications Warehouse

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

2003-01-01

Diffuse reflectance spectra of 15 mineral species commonly associated with sulphide-bearing mine wastes show diagnostic absorption bands related to electronic processes involving ferric and/or ferrous iron, and to vibrational processes involving water and hydroxyl. Many of these absorption bands are relatively broad and overlapping; however, spectral analysis methods, including continuum removal and derivative analysis, permit most of the minerals to be distinguished. Key spectral differences between the minerals are illustrated in a series of plots showing major absorption band centres and other spectral feature positions. Because secondary iron minerals are sensitive indicators of pH, Eh, relative humidity, and other environmental conditions, spectral mapping of mineral distributions promises to have important application to mine waste remediation studies.

Ultraviolet to optical spectral distributions of northern star-forming galaxies

NASA Technical Reports Server (NTRS)

Mcquade, Kerry; Calzetti, Daniela; Kinney, Anne L.

1995-01-01

We report spectral energy distribution from the UV to the optical for a sample of 31 northern star-forming galaxies. We also present measurements for emission-line fluxes, continuum levels, and equivalent widths of absorption features for each individual spectrum as well as averages for the eight galactic activity classes, including normal, starburst, Seyfert 2, blue compact dwarf, blue compact, Low-Inonization Nuclear Emission Regions (LINER), H II, and combination LINER-H II galaxies.

Reflectance spectroscopy (350-2500 nm) of solid-state polycyclic aromatic hydrocarbons (PAHs)

NASA Astrophysics Data System (ADS)

Izawa, M. R. M.; Applin, D. M.; Norman, L.; Cloutis, E. A.

2014-07-01

Polycyclic aromatic hydrocarbons (PAHs) are organic compounds based on fused aromatic rings, and are formed in a variety of astrophysical, solar nebula and planetary processes. Polycyclic aromatic hydrocarbons are known or suspected to occur in a wide variety of planetary settings including icy satellites, Titan’s hazes, carbonaceous meteorites, comet nuclei, ring particles; and terrestrial organic-rich lithologies such as coals, asphaltites, and bituminous sands. Relatively few measurements of the visible and near-infrared spectra of PAHs exist, yet this wavelength region (350-2500 nm) is widely used for remote sensing. This study presents detailed analyses of the 350-2500 nm reflectance spectra of 47 fine-grained powders of different high-purity solid-state PAHs. Spectral properties of PAHs change with variations in the number and connectivity of linked aromatic rings and the presence and type of side-groups and heterocycles. PAH spectra are characterized by three strong features near ∼880 nm, ∼1145 nm, and ∼1687 nm due to overtones of νCH fundamental stretching vibrations. Some PAHs are amenable to remote detection due to the presence of diagnostic spectral features, including: Nsbnd H stretching overtones at 1490-1515 nm in NH- and NH2-bearing PAHs, aliphatic or saturated bond Csbnd H overtone vibrations at ∼1180-1280 nm and ∼1700-1860 nm; a broad asymmetric feature between ∼1450 nm and ∼1900 nm due to Osbnd H stretching overtones in aromatic alcohols, Csbnd H and Cdbnd O combinations near ∼2000-2010 nm and ∼2060-2270 nm in acetyl and carboxyl-bearing PAHs. Other substituents such as sulphonyl, thioether ether and carboxyl heterocycles, or cyano, nitrate, and aromatic side groups, do not produce well-resolved diagnostic spectral features but do cause shifts in the positions of the aromatic Csbnd H vibrational overtone features. Fluorescence is commonly suppressed by the presence of heterocycles, side-groups and in many non-alternant PAHs. The spectral characteristics of PAHs offer the potential, under suitable circumstances, for remote characterization of the classes of PAH present and in some cases, identification of particular heterocyclic or side-group substituents.

AKARI/IRC NEAR-INFRARED SPECTRAL ATLAS OF GALACTIC PLANETARY NEBULAE

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

Ohsawa, Ryou; Onaka, Takashi; Sakon, Itsuki

2016-04-15

Near-infrared (2.5–5.0 μm) low-resolution (λ/Δλ ∼ 100) spectra of 72 Galactic planetary nebulae (PNe) were obtained with the Infrared Camera (IRC) in the post-helium phase. The IRC, equipped with a 1′ × 1′ window for spectroscopy of a point source, was capable of obtaining near-infrared spectra in a slit-less mode without any flux loss due to a slit. The spectra show emission features including hydrogen recombination lines and the 3.3–3.5 μm hydrocarbon features. The intensity and equivalent width of the emission features were measured by spectral fitting. We made a catalog providing unique information on the investigation of the near-infrared emission ofmore » PNe. In this paper, details of the observations and characteristics of the catalog are described.« less

Automatic identification of land uses from ERTS-1 data obtained over Milwaukee, Wisconsin

NASA Technical Reports Server (NTRS)

Baumgardner, M. F.; Landgrebe, D. A. (Principal Investigator); Kramer, H. H.

1972-01-01

The author has identified the following significant results. Spectrally, thirteen classes of ground cover were identified within Milwaukee County: five classes of water, grassy open areas, beach, two classes of road, woods, suburban, inner city, and industry. A distinct concentric pattern of land use was identified in the county radiating outward from the central business district. The first ring has a principal feature, termed the inner city, which is indicative of the older part of the county. In the second ring, the land use becomes more complex, consisting of suburban areas, parks, and varied institutional features. The third general ring consists primarily of open, grassy land, with scattered residential subdivisions, wood lots, and small water bodies. The five classes of water identified suggest differences in depth, turbidity, and/or color. A number of major roads were identified. Other spectrally identifiable features included the larger county parks and larger cemeteries.

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.

Emergent spectral properties of river network topology: an optimal channel network approach.

PubMed

Abed-Elmdoust, Armaghan; Singh, Arvind; Yang, Zong-Liang

2017-09-13

Characterization of river drainage networks has been a subject of research for many years. However, most previous studies have been limited to quantities which are loosely connected to the topological properties of these networks. In this work, through a graph-theoretic formulation of drainage river networks, we investigate the eigenvalue spectra of their adjacency matrix. First, we introduce a graph theory model for river networks and explore the properties of the network through its adjacency matrix. Next, we show that the eigenvalue spectra of such complex networks follow distinct patterns and exhibit striking features including a spectral gap in which no eigenvalue exists as well as a finite number of zero eigenvalues. We show that such spectral features are closely related to the branching topology of the associated river networks. In this regard, we find an empirical relation for the spectral gap and nullity in terms of the energy dissipation exponent of the drainage networks. In addition, the eigenvalue distribution is found to follow a finite-width probability density function with certain skewness which is related to the drainage pattern. Our results are based on optimal channel network simulations and validated through examples obtained from physical experiments on landscape evolution. These results suggest the potential of the spectral graph techniques in characterizing and modeling river networks.

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.

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.

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.

Type II Supernova Spectral Diversity. I. Observations, Sample Characterization, and Spectral Line Evolution

NASA Astrophysics Data System (ADS)

Gutiérrez, Claudia P.; Anderson, Joseph P.; Hamuy, Mario; Morrell, Nidia; González-Gaitan, Santiago; Stritzinger, Maximilian D.; Phillips, Mark M.; Galbany, Lluis; Folatelli, Gastón; Dessart, Luc; Contreras, Carlos; Della Valle, Massimo; Freedman, Wendy L.; Hsiao, Eric Y.; Krisciunas, Kevin; Madore, Barry F.; Maza, José; Suntzeff, Nicholas B.; Prieto, Jose Luis; González, Luis; Cappellaro, Enrico; Navarrete, Mauricio; Pizzella, Alessandro; Ruiz, Maria T.; Smith, R. Chris; Turatto, Massimo

2017-11-01

We present 888 visual-wavelength spectra of 122 nearby type II supernovae (SNe II) obtained between 1986 and 2009, and ranging between 3 and 363 days post-explosion. In this first paper, we outline our observations and data reduction techniques, together with a characterization based on the spectral diversity of SNe II. A statistical analysis of the spectral matching technique is discussed as an alternative to nondetection constraints for estimating SN explosion epochs. The time evolution of spectral lines is presented and analyzed in terms of how this differs for SNe of different photometric, spectral, and environmental properties: velocities, pseudo-equivalent widths, decline rates, magnitudes, time durations, and environment metallicity. Our sample displays a large range in ejecta expansion velocities, from ˜9600 to ˜1500 km s-1 at 50 days post-explosion with a median {{{H}}}α value of 7300 km s-1. This is most likely explained through differing explosion energies. Significant diversity is also observed in the absolute strength of spectral lines, characterized through their pseudo-equivalent widths. This implies significant diversity in both temperature evolution (linked to progenitor radius) and progenitor metallicity between different SNe II. Around 60% of our sample shows an extra absorption component on the blue side of the {{{H}}}α P-Cygni profile (“Cachito” feature) between 7 and 120 days since explosion. Studying the nature of Cachito, we conclude that these features at early times (before ˜35 days) are associated with Si II λ 6355, while past the middle of the plateau phase they are related to high velocity (HV) features of hydrogen lines. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile; and the Gemini Observatory, Cerro Pachon, Chile (Gemini Program GS-2008B-Q-56). Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile (ESO Programs 076.A-0156, 078.D-0048, 080.A-0516, and 082.A-0526).

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.

Feature level fusion for enhanced geological mapping of ophiolile complex using ASTER and Landsat TM data

NASA Astrophysics Data System (ADS)

Pournamdari, M.; Hashim, M.

2014-02-01

Chromite ore deposit occurrence is related to ophiolite complexes as a part of the oceanic crust and provides a good opportunity for lithological mapping using remote sensing data. The main contribution of this paper is a novel approaches to discriminate different rock units associated with ophiolite complex using the Feature Level Fusion technique on ASTER and Landsat TM satellite data at regional scale. In addition this study has applied spectral transform approaches, consisting of Spectral Angle Mapper (SAM) to distinguish the concentration of high-potential areas of chromite and also for determining the boundary between different rock units. Results indicated both approaches show superior outputs compared to other methods and can produce a geological map for ophiolite complex rock units in the arid and the semi-arid region. The novel technique including feature level fusion and Spectral Angle Mapper (SAM) discriminated ophiolitic rock units and produced detailed geological maps of the study area. As a case study, Sikhoran ophiolite complex located in SE, Iran has been selected for image processing techniques. In conclusion, a suitable approach for lithological mapping of ophiolite complexes is demonstrated, this technique contributes meaningfully towards economic geology in terms of identifying new prospects.

Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy.

PubMed

Yang, Guang; Nawaz, Tahir; Barrick, Thomas R; Howe, Franklyn A; Slabaugh, Greg

2015-12-01

Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

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

Defining and Detecting Complex Peak Relationships in Mass Spectral Data: The Mz.unity Algorithm.

PubMed

Mahieu, Nathaniel G; Spalding, Jonathan L; Gelman, Susan J; Patti, Gary J

2016-09-20

Analysis of a single analyte by mass spectrometry can result in the detection of more than 100 degenerate peaks. These degenerate peaks complicate spectral interpretation and are challenging to annotate. In mass spectrometry-based metabolomics, this degeneracy leads to inflated false discovery rates, data sets containing an order of magnitude more features than analytes, and an inefficient use of resources during data analysis. Although software has been introduced to annotate spectral degeneracy, current approaches are unable to represent several important classes of peak relationships. These include heterodimers and higher complex adducts, distal fragments, relationships between peaks in different polarities, and complex adducts between features and background peaks. Here we outline sources of peak degeneracy in mass spectra that are not annotated by current approaches and introduce a software package called mz.unity to detect these relationships in accurate mass data. Using mz.unity, we find that data sets contain many more complex relationships than we anticipated. Examples include the adduct of glutamate and nicotinamide adenine dinucleotide (NAD), fragments of NAD detected in the same or opposite polarities, and the adduct of glutamate and a background peak. Further, the complex relationships we identify show that several assumptions commonly made when interpreting mass spectral degeneracy do not hold in general. These contributions provide new tools and insight to aid in the annotation of complex spectral relationships and provide a foundation for improved data set identification. Mz.unity is an R package and is freely available at https://github.com/nathaniel-mahieu/mz.unity as well as our laboratory Web site http://pattilab.wustl.edu/software/ .

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.

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.

Assessment of geostatistical features for object-based image classification of contrasted landscape vegetation cover

NASA Astrophysics Data System (ADS)

de Oliveira Silveira, Eduarda Martiniano; de Menezes, Michele Duarte; Acerbi Júnior, Fausto Weimar; Castro Nunes Santos Terra, Marcela; de Mello, José Márcio

2017-07-01

Accurate mapping and monitoring of savanna and semiarid woodland biomes are needed to support the selection of areas of conservation, to provide sustainable land use, and to improve the understanding of vegetation. The potential of geostatistical features, derived from medium spatial resolution satellite imagery, to characterize contrasted landscape vegetation cover and improve object-based image classification is studied. The study site in Brazil includes cerrado sensu stricto, deciduous forest, and palm swamp vegetation cover. Sentinel 2 and Landsat 8 images were acquired and divided into objects, for each of which a semivariogram was calculated using near-infrared (NIR) and normalized difference vegetation index (NDVI) to extract the set of geostatistical features. The features selected by principal component analysis were used as input data to train a random forest algorithm. Tests were conducted, combining spectral and geostatistical features. Change detection evaluation was performed using a confusion matrix and its accuracies. The semivariogram curves were efficient to characterize spatial heterogeneity, with similar results using NIR and NDVI from Sentinel 2 and Landsat 8. Accuracy was significantly greater when combining geostatistical features with spectral data, suggesting that this method can improve image classification results.

A novel scheme for abnormal cell detection in Pap smear images

NASA Astrophysics Data System (ADS)

Zhao, Tong; Wachman, Elliot S.; Farkas, Daniel L.

2004-07-01

Finding malignant cells in Pap smear images is a "needle in a haystack"-type problem, tedious, labor-intensive and error-prone. It is therefore desirable to have an automatic screening tool in order that human experts can concentrate on the evaluation of the more difficult cases. Most research on automatic cervical screening tries to extract morphometric and texture features at the cell level, in accordance with the NIH "The Bethesda System" rules. Due to variances in image quality and features, such as brightness, magnification and focus, morphometric and texture analysis is insufficient to provide robust cervical cancer detection. Using a microscopic spectral imaging system, we have produced a set of multispectral Pap smear images with wavelengths from 400 nm to 690 nm, containing both spectral signatures and spatial attributes. We describe a novel scheme that combines spatial information (including texture and morphometric features) with spectral information to significantly improve abnormal cell detection. Three kinds of wavelet features, orthogonal, bi-orthogonal and non-orthogonal, are carefully chosen to optimize recognition performance. Multispectral feature sets are then extracted in the wavelet domain. Using a Back-Propagation Neural Network classifier that greatly decreases the influence of spurious events, we obtain a classification error rate of 5%. Cell morphometric features, such as area and shape, are then used to eliminate most remaining small artifacts. We report initial results from 149 cells from 40 separate image sets, in which only one abnormal cell was missed (TPR = 97.6%) and one normal cell was falsely classified as cancerous (FPR = 1%).

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.

Classification of normal and malignant human gastric mucosa tissue with confocal Raman microspectroscopy and wavelet analysis

NASA Astrophysics Data System (ADS)

Hu, Yaogai; Shen, Aiguo; Jiang, Tao; Ai, Yong; Hu, Jiming

2008-02-01

Thirty-two samples from the human gastric mucosa tissue, including 13 normal and 19 malignant tissue samples were measured by confocal Raman microspectroscopy. The low signal-to-background ratio spectra from human gastric mucosa tissues were obtained by this technique without any sample preparation. Raman spectral interferences include a broad featureless sloping background due to fluorescence and noise. They mask most Raman spectral feature and lead to problems with precision and quantitation of the original spectral information. A preprocessed algorithm based on wavelet analysis was used to reduce noise and eliminate background/baseline of Raman spectra. Comparing preprocessed spectra of malignant gastric mucosa tissues with those of counterpart normal ones, there were obvious spectral changes, including intensity increase at ˜1156 cm -1 and intensity decrease at ˜1587 cm -1. The quantitative criterion based upon the intensity ratio of the ˜1156 and ˜1587 cm -1 was extracted for classification of the normal and malignant gastric mucosa tissue samples. This could result in a new diagnostic method, which would assist the early diagnosis of gastric cancer.

Enhanced lines and box-shaped features in the gamma-ray spectrum from annihilating dark matter in the NMSSM

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

Cerdeño, D.G.; Peiró, M.; Robles, S., E-mail: davidg.cerdeno@gmail.com, E-mail: miguel.peiro@uam.es, E-mail: sandra.robles@uam.es

2016-04-01

We study spectral features in the gamma-ray emission from dark matter (DM) annihilation in the Next-to-Minimal Supersymmetric Standard Model (NMSSM), with either neutralino or right-handed (RH) sneutrino DM . We perform a series of scans over the NMSSM parameter space, compute the DM annihilation cross section into two photons and the contribution of box-shaped features, and compare them with the limits derived from the Fermi-LAT search for gamma-ray lines using the latest Pass 8 data. We implement the LHC bounds on the Higgs sector and on the masses of supersymmetric particles as well as the constraints on low-energy observables. Wemore » also consider the recent upper limits from the Fermi-LAT satellite on the continuum gamma-ray emission from dwarf spheroidal galaxies (dSphs). We show that in the case of the RH sneutrino the constraint on gamma-ray spectral features can be more stringent than the dSph bounds. This is due to the Breit-Wigner enhancement near the ubiquitous resonances with a CP even Higgs and the contribution of scalar and pseudoscalar Higgs final states to box-shaped features. By contrast, for neutralino DM, the di-photon final state is only enhanced in the resonance with a Z boson and box-shaped features are even more suppressed. Therefore, the observation of spectral features could constitute a discriminating factor between both models. In addition, we compare our results with direct DM searches, including the SuperCDMS and LUX limits on the elastic DM-nucleus scattering cross section and show that some of these scenarios would be accessible to next generation experiments. Thus, our findings strengthen the idea of complementarity among distinct DM search strategies.« less

Spectral reflectances of natural targets for use in remote sensing studies

NASA Technical Reports Server (NTRS)

Bowker, D. E.; Davis, R. E.; Myrick, D. L.; Stacy, K.; Jones, W. T.

1985-01-01

A collection of spectral reflectances of 156 natural targets is presented in a uniform format. For each target both a graphical plot and a digital tabulation of reflectance is given. The data were taken from the literature and include laboratory, field, and aircraft measurements. A discussion of the different measurements of reflectance is given, along with the changes in apparent reflectance when targets are viewed through the atmosphere. The salient features of the reflectance curves of common target types are presented and discussed.

CCFpams: Atmospheric stellar parameters from cross-correlation functions

NASA Astrophysics Data System (ADS)

Malavolta, Luca; Lovis, Christophe; Pepe, Francesco; Sneden, Christopher; Udry, Stephane

2017-07-01

CCFpams allows the measurement of stellar temperature, metallicity and gravity within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, the technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. Literature stellar parameters of high signal-to-noise (SNR) and high-resolution HARPS spectra of FGK Main Sequence stars are used to calibrate the stellar parameters as a function of CCF areas.

Assessing the performance of multiple spectral-spatial features of a hyperspectral image for classification of urban land cover classes using support vector machines and artificial neural network

NASA Astrophysics Data System (ADS)

Pullanagari, Reddy; Kereszturi, Gábor; Yule, Ian J.; Ghamisi, Pedram

2017-04-01

Accurate and spatially detailed mapping of complex urban environments is essential for land managers. Classifying high spectral and spatial resolution hyperspectral images is a challenging task because of its data abundance and computational complexity. Approaches with a combination of spectral and spatial information in a single classification framework have attracted special attention because of their potential to improve the classification accuracy. We extracted multiple features from spectral and spatial domains of hyperspectral images and evaluated them with two supervised classification algorithms; support vector machines (SVM) and an artificial neural network. The spatial features considered are produced by a gray level co-occurrence matrix and extended multiattribute profiles. All of these features were stacked, and the most informative features were selected using a genetic algorithm-based SVM. After selecting the most informative features, the classification model was integrated with a segmentation map derived using a hidden Markov random field. We tested the proposed method on a real application of a hyperspectral image acquired from AisaFENIX and on widely used hyperspectral images. From the results, it can be concluded that the proposed framework significantly improves the results with different spectral and spatial resolutions over different instrumentation.

Hyperspectral image classification by a variable interval spectral average and spectral curve matching combined algorithm

NASA Astrophysics Data System (ADS)

Senthil Kumar, A.; Keerthi, V.; Manjunath, A. S.; Werff, Harald van der; Meer, Freek van der

2010-08-01

Classification of hyperspectral images has been receiving considerable attention with many new applications reported from commercial and military sectors. Hyperspectral images are composed of a large number of spectral channels, and have the potential to deliver a great deal of information about a remotely sensed scene. However, in addition to high dimensionality, hyperspectral image classification is compounded with a coarse ground pixel size of the sensor for want of adequate sensor signal to noise ratio within a fine spectral passband. This makes multiple ground features jointly occupying a single pixel. Spectral mixture analysis typically begins with pixel classification with spectral matching techniques, followed by the use of spectral unmixing algorithms for estimating endmembers abundance values in the pixel. The spectral matching techniques are analogous to supervised pattern recognition approaches, and try to estimate some similarity between spectral signatures of the pixel and reference target. In this paper, we propose a spectral matching approach by combining two schemes—variable interval spectral average (VISA) method and spectral curve matching (SCM) method. The VISA method helps to detect transient spectral features at different scales of spectral windows, while the SCM method finds a match between these features of the pixel and one of library spectra by least square fitting. Here we also compare the performance of the combined algorithm with other spectral matching techniques using a simulated and the AVIRIS hyperspectral data sets. Our results indicate that the proposed combination technique exhibits a stronger performance over the other methods in the classification of both the pure and mixed class pixels simultaneously.

Hyperspectral fundus imager

NASA Astrophysics Data System (ADS)

Truitt, Paul W.; Soliz, Peter; Meigs, Andrew D.; Otten, Leonard John, III

2000-11-01

A Fourier Transform hyperspectral imager was integrated onto a standard clinical fundus camera, a Zeiss FF3, for the purposes of spectrally characterizing normal anatomical and pathological features in the human ocular fundus. To develop this instrument an existing FDA approved retinal camera was selected to avoid the difficulties of obtaining new FDA approval. Because of this, several unusual design constraints were imposed on the optical configuration. Techniques to calibrate the sensor and to define where the hyperspectral pushbroom stripe was located on the retina were developed, including the manufacturing of an artificial eye with calibration features suitable for a spectral imager. In this implementation the Fourier transform hyperspectral imager can collect over a hundred 86 cm-1 spectrally resolved bands with 12 micro meter/pixel spatial resolution within the 1050 nm to 450 nm band. This equates to 2 nm to 8 nm spectral resolution depending on the wavelength. For retinal observations the band of interest tends to lie between 475 nm and 790 nm. The instrument has been in use over the last year successfully collecting hyperspectral images of the optic disc, retinal vessels, choroidal vessels, retinal backgrounds, and macula diabetic macular edema, and lesions of age-related macular degeneration.

IR spectroscopic characteristics of cell cycle and cell death probed by synchrotron radiation based Fourier transform IR spectromicroscopy

NASA Technical Reports Server (NTRS)

Holman, H. Y.; Martin, M. C.; Blakely, E. A.; Bjornstad, K.; McKinney, W. R.

2000-01-01

Synchrotron radiation based Fourier transform IR (SR-FTIR) spectromicroscopy allows the study of individual living cells with a high signal to noise ratio. Here we report the use of the SR-FTIR technique to investigate changes in IR spectral features from individual human lung fibroblast (IMR-90) cells in vitro at different points in their cell cycle. Clear changes are observed in the spectral regions corresponding to proteins, DNA, and RNA as a cell changes from the G(1)-phase to the S-phase and finally into mitosis. These spectral changes include markers for the changing secondary structure of proteins in the cell, as well as variations in DNA/RNA content and packing as the cell cycle progresses. We also observe spectral features that indicate that occasional cells are undergoing various steps in the process of cell death. The dying or dead cell has a shift in the protein amide I and II bands corresponding to changing protein morphologies, and a significant increase in the intensity of an ester carbonyl C===O peak at 1743 cm(-1) is observed. Copyright John Wiley & Sons, Inc. Biopolymers (Biospectroscopy) 57: 329-335, 2000.

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.

Intelligent image processing for vegetation classification using multispectral LANDSAT data

NASA Astrophysics Data System (ADS)

Santos, Stewart R.; Flores, Jorge L.; Garcia-Torales, G.

2015-09-01

We propose an intelligent computational technique for analysis of vegetation imaging, which are acquired with multispectral scanner (MSS) sensor. This work focuses on intelligent and adaptive artificial neural network (ANN) methodologies that allow segmentation and classification of spectral remote sensing (RS) signatures, in order to obtain a high resolution map, in which we can delimit the wooded areas and quantify the amount of combustible materials present into these areas. This could provide important information to prevent fires and deforestation of wooded areas. The spectral RS input data, acquired by the MSS sensor, are considered in a random propagation remotely sensed scene with unknown statistics for each Thematic Mapper (TM) band. Performing high-resolution reconstruction and adding these spectral values with neighbor pixels information from each TM band, we can include contextual information into an ANN. The biggest challenge in conventional classifiers is how to reduce the number of components in the feature vector, while preserving the major information contained in the data, especially when the dimensionality of the feature space is high. Preliminary results show that the Adaptive Modified Neural Network method is a promising and effective spectral method for segmentation and classification in RS images acquired with MSS sensor.

Statistical analysis and machine learning algorithms for optical biopsy

NASA Astrophysics Data System (ADS)

Wu, Binlin; Liu, Cheng-hui; Boydston-White, Susie; Beckman, Hugh; Sriramoju, Vidyasagar; Sordillo, Laura; Zhang, Chunyuan; Zhang, Lin; Shi, Lingyan; Smith, Jason; Bailin, Jacob; Alfano, Robert R.

2018-02-01

Analyzing spectral or imaging data collected with various optical biopsy methods is often times difficult due to the complexity of the biological basis. Robust methods that can utilize the spectral or imaging data and detect the characteristic spectral or spatial signatures for different types of tissue is challenging but highly desired. In this study, we used various machine learning algorithms to analyze a spectral dataset acquired from human skin normal and cancerous tissue samples using resonance Raman spectroscopy with 532nm excitation. The algorithms including principal component analysis, nonnegative matrix factorization, and autoencoder artificial neural network are used to reduce dimension of the dataset and detect features. A support vector machine with a linear kernel is used to classify the normal tissue and cancerous tissue samples. The efficacies of the methods are compared.

Depth resolved hyperspectral imaging spectrometer based on structured light illumination and Fourier transform interferometry

PubMed Central

Choi, Heejin; Wadduwage, Dushan; Matsudaira, Paul T.; So, Peter T.C.

2014-01-01

A depth resolved hyperspectral imaging spectrometer can provide depth resolved imaging both in the spatial and the spectral domain. Images acquired through a standard imaging Fourier transform spectrometer do not have the depth-resolution. By post processing the spectral cubes (x, y, λ) obtained through a Sagnac interferometer under uniform illumination and structured illumination, spectrally resolved images with depth resolution can be recovered using structured light illumination algorithms such as the HiLo method. The proposed scheme is validated with in vitro specimens including fluorescent solution and fluorescent beads with known spectra. The system is further demonstrated in quantifying spectra from 3D resolved features in biological specimens. The system has demonstrated depth resolution of 1.8 μm and spectral resolution of 7 nm respectively. PMID:25360367

Extending the McDonald Observatory Serendipitous Survey of UV/Blue Asteroid Spectra

NASA Technical Reports Server (NTRS)

Vilas, Faith; Cochran, A. L.

1999-01-01

Moderate resolution asteroid spectra in the 350 - 650 nm spectral range acquired randomly over many years (Cochran and Vilas, Icarus v 127, 121, 1997) identified absorption features in spectra of some of the asteroids. A feature centered at 430 nm was identified in the spectra of some low-albedo asteroids (C class and subclass), similar to the feature identified by Vilas et al. (Icarus, v. 102, 225,1993) in other low-albedo asteroid spectra and attributed to a ferric iron spin-forbidden transition in iron alteration minerals such as jarosite. Features at 505 nm and 430 nm were identified in the spectrum of 4 Vesta. The 505-nm feature is highly diagnostic of the amount and form of calcium in pyroxenes. This suggested further research on the sharpness and spectral placement of this feature in the spectra of Vesta and Vestoids (e.g., Cochran and Vilas, Icarus v. 134, 207, 1998). In 1997 and 1998, additional UV/blue spectra were obtained at the 2.7-m Harlan J. Smith telescope with a facility cassegrain spectrograph. These included spectra of low-albedo asteroids, the R-class asteroid 349 Dembowska, and the M-class asteroid 135 Hertha. These spectra will be presented and identified features will be discussed.

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.

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Spectral discrimination of macrophyte species during different seasons in a tropical wetland using in-situ hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Saluja, Ridhi; Garg, J. K.

2017-10-01

Wetlands, one of the most productive ecosystems on Earth, perform myriad ecological functions and provide a host of ecological services. Despite their ecological and economic values, wetlands have experienced significant degradation during the last century and the trend continues. Hyperspectral sensors provide opportunities to map and monitor macrophyte species within wetlands for their management and conservation. In this study, an attempt has been made to evaluate the potential of narrowband spectroradiometer data in discriminating wetland macrophytes during different seasons. main objectives of the research were (1) to determine whether macrophyte species could be discriminated based on in-situ hyperspectral reflectance collected over different seasons and at each measured waveband (400-950nm), (2) to compare the effectiveness of spectral reflectance and spectral indices in discriminating macrophyte species, and (3) to identify spectral wavelengths that are most sensitive in discriminating macrophyte species. Spectral characteristics of dominant wetland macrophyte species were collected seasonally using SVC GER 1500 portable spectroradiometer over the 400 to 1050nm spectral range at 1.5nm interval, at the Bhindawas wetland in the state of Haryana, India. Hyperspectral observations were pre-processed and subjected to statistical analysis, which involved a two-step approach including feature selection (ANOVA and KW test) and feature extraction (LDA and PCA). Statistical analysis revealed that the most influential wavelengths for discrimination were distributed along the spectral profile from visible to the near-infrared regions. The results suggest that hyperspectral data can be used discriminate wetland macrophyte species working as an effective tool for advanced mapping and monitoring of wetlands.

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.

Hydrothermally-altered dacite terrains in the Methana peninsula Greece: Relevance to Mars

NASA Astrophysics Data System (ADS)

Cloutis, Edward A.; Jonatanson, Victoria; Bandfield, Joshua L.; Amador, Elena S.; Rivera-Hernández, Frances; Mann, P.; Mertzman, Stanley A.

2017-04-01

Dacitic rocks, often indicative of crustal recycling on Earth, have been identified in some regions on Mars, as have possible hydrothermally/aqueously-altered dacites. To enable more robust identification of unaltered and altered dacites on Mars and other planetary bodies, we undertook a spectroscopic-structural-compositional study of altered and unaltered dacites from a dacitic volcanic region in Methana, Greece. Dacites erupted in this region range from fresh to pervasively hydrothermally altered, resulting in friable, Si-enriched products, as well as fumarolic deposition of Si and S-rich precipitates. Spectrally, fresh dacites are unremarkable in the 0.35-2.5 μm region with low, generally flat, reflectance and few, if any, absorption bands. Dacite infrared spectra exhibit Si-O absorption features in the 8-10 μm region (which are characteristic of Si-bearing rocks, in general). With increasing alteration, reflectance over the 0.35-2.5 μm range increases, absorption bands in the 1.4 and 1.9 μm region, associated with H2O/OH, and in the 2.2-2.3 μm region, associated with SiOH, become deeper, Fe3+-associated absorption bands in the 0.43 and 0.9 μm region appear, and the Christiansen feature near 8 μm moves to shorter wavelengths. Silica-rich coatings appear to be spectrally indistinguishable from Si-rich alteration. Alteration-formed sulfates may be detectable by the presence of diagnostic absorption features in the 0.35-2.5 μm region. Spectral similarities between different poorly crystalline high-Si phases make it difficult to uniquely determine the processes that formed high-Si surfaces that have been identified on Mars. However, the samples described here show a variety of spectral features that correspond to variable amounts of alteration. We find a similar range of spectral features, likely due to similar phases, on Mars, perhaps indicating a similar range of alteration environments. Comparison of laboratory spectra to Mars observational data also suggests that the major Si-rich regions likely consist of assemblages that more mineralogically complex than those included in this study.

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.

Coordinated analyses of orbital and spirit rover data to characterize surface materials on the cratered plains of Gusev Crater, Mars

USGS Publications Warehouse

Lichtenberg, K.A.; Arvidson, R. E.; Poulet, F.; Morris, R.V.; Knudson, A.; Bell, J.F.; Bellucci, G.; Bibring, J.-P.; Farrand, W. H.; Johnson, J. R.; Ming, D. W.; Pinet, P.C.; Rogers, A.D.; Squyres, S. W.

2007-01-01

Comparison of the Mars Exploration Rover Spirit's Pancam (0.4 to 1.0 ??m) and Mars Express Observatoire pour la Mineralogie l'Eau, les Glaces et l'Activite?? (OMEGA) (0.4 to 2.5 ??m) spectral reflectance data over Spirit's traverses shows that Gusev cratered plains are dominated by nanophase ferric-oxide-rich dust covering weakly altered basaltic sands. This interpretation is also consistent with both observations from OMEGA data covering plains beyond the traverse region and interpretations of data from the other payload instruments on the Spirit Rover. OMEGA observations of relatively low albedo regions where dust has presumably been stripped by dust devils show negative spectral reflectance slopes from 1.5 to 2.5 ??m and moderately masked spectral features which are indicative of olivine or pyroxene. High-albedo regions north and south of the Spirit landing site have flat spectral reflectance slopes and few spectral features, although all spectra have a nanophase ferric-oxide absorption edge between 0.4 and 0.75 ??m. Comparison of THEMIS-derived thermal inertia values with OMEGA-derived spectral parameters shows that although the dust cover can be optically thick (0.4 to 2.5 ??m wavelength region) in some areas, it is not thick enough (???1 cm) to mask the thermal inertia of the underlying substrate for areas included in this study. Copyright 2007 by the American Geophysical Union.

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.

Infrared Space Observatory Observations of Far-Infrared Rotational Emission Lines of Water Vapor toward the Supergiant Star VY Canis Majoris

NASA Astrophysics Data System (ADS)

Neufeld, David A.; Feuchtgruber, Helmut; Harwit, Martin; Melnick, Gary J.

1999-06-01

We report the detection of numerous far-infrared emission lines of water vapor toward the supergiant star VY Canis Majoris. A 29.5-45 μm grating scan of VY CMa, obtained using the Short-Wavelength Spectrometer (SWS) of the Infrared Space Observatory at a spectral resolving power λ/Δλ of ~2000, reveals at least 41 spectral features due to water vapor that together radiate a total luminosity of ~25 Lsolar. In addition to pure rotational transitions within the ground vibrational state, these features include rotational transitions within the (010) excited vibrational state. The spectrum also shows the 2Π1/2(J=5/2)<--2Π3/2(J=3/2) OH feature near 34.6 μm in absorption. Additional SWS observations of VY CMa were carried out in the instrument's Fabry-Perot mode for three water transitions: the 725-616 line at 29.8367 μm, the 441-312 line at 31.7721 μm, and the 432-303 line at 40.6909 μm. The higher spectral resolving power λ/Δλ of approximately 30,000 thereby obtained permits the line profiles to be resolved spectrally for the first time and reveals the ``P Cygni'' profiles that are characteristic of emission from an outflowing envelope. Based on observations with ISO, an ESA project with instruments funded by ESA Member States (especially the PI countries: France, Germany, the Netherlands, and the UK) with the participation of ISAS and NASA.

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.

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.

Reflection spectra and magnetochemistry of iron oxides and natural surfaces

NASA Technical Reports Server (NTRS)

Wasilewski, P.

1978-01-01

The magnetic properties and spectral characteristics of iron oxides are distinctive. Diagnostic features in reflectance spectra (0.5 to 2.4 micron) for alpha Fe2O3, gamma Fe2O3, and FeOOH include location of Fe3(+) absorption features, intensity ratios at various wavelengths, and the curve shape between 1.2 micron and 2.4 micron. The reflection spectrum of natural rock surfaces are seldom those of the bulk rock because of weathering effects. Coatings are found to be dominated by iron oxides and clay. A simple macroscopic model of rock spectra (based on concepts of stains and coatings) is considered adequate for interpretation of LANDSAT data. The magnetic properties of materials associated with specific spectral types and systematic changes in both spectra and magnetic properties are considered.

Spontaneous emission near the edge of a photonic band gap

NASA Astrophysics Data System (ADS)

John, Sajeev; Quang, Tran

1994-08-01

The spectral and dynamical features of spontaneous emission from two and three-level atoms in which one transition frequency lay near the edge of a photonic band gap (PBG) were derived. These features included temporal oscillations, fractionalized steady-state atomic population on the excited state, spectral splitting and subnatural bandwidth. The effect of N-1 unexcited atoms were also taken into account. The direct consequences of photon localization as embodied in the photon-atom bound state were observed. One feasible experimental accomplishment of these effects may ensue from laser-cooled atoms in the void regions of a PBG medium. Another option is the application of an organic impurity molecule such as pentacene. Such molecules were known to show extremely narrow linewidths when placed in fitting solid hosts.

Quasiparticle spectra from molecules to bulk

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

Vlček, Vojtěch; Rabani, Eran; Neuhauser, Daniel

We present a stochastic cumulant GW method, allowing us to map the evolution of photoemission spectra, quasiparticle energies, lifetimes, and emergence of collective excitations from molecules to bulklike systems with up to thousands of valence electrons, including Si nanocrystals and nanoplatelets. The quasiparticle energies rise due to their coupling with collective shake-up (plasmon) excitations, and this coupling leads to significant spectral weight loss (up to 50% for the low-energy states), shortening the lifetimes and shifting the spectral features to lower energies by as much as 0.6 eV. Such features are common to all the systems studied irrespective of their sizesmore » and shapes. For small and low-dimensional systems the surface plasmon resonances affect the frequency of the collective excitation and position of the satellites.« less

Topics in Astrophysical X-Ray and Gamma Ray Spectroscopy. Ph.D. Thesis - Maryland Univ.

NASA Technical Reports Server (NTRS)

Bussard, R. W.

1978-01-01

A number of topics relating to astrophysical observations that have already been made or are currently planned of spectral features, mostly emission lines, in the X-ray and gamma ray region of the electromagnetic spectrum are investigated. These topics include: the production of characteristic X-ray and gamma ray lines by nonthermal ions, spectral features induced by processes occurring in strong magnetic fields, and the positron annihilation line at 0.5 MeV. The rate of X-ray production at 6.8 keV by the 2p to 1s transition in fast hydrogen- and helium-like iron ions, following both electron capture to excited levels and collisional excitation is calculated. The cross section for electron-ion Coulomb collisions in strong fields is also calculated.

Quasiparticle spectra from molecules to bulk

DOE PAGES

Vlček, Vojtěch; Rabani, Eran; Neuhauser, Daniel

2018-03-16

We present a stochastic cumulant GW method, allowing us to map the evolution of photoemission spectra, quasiparticle energies, lifetimes, and emergence of collective excitations from molecules to bulklike systems with up to thousands of valence electrons, including Si nanocrystals and nanoplatelets. The quasiparticle energies rise due to their coupling with collective shake-up (plasmon) excitations, and this coupling leads to significant spectral weight loss (up to 50% for the low-energy states), shortening the lifetimes and shifting the spectral features to lower energies by as much as 0.6 eV. Such features are common to all the systems studied irrespective of their sizesmore » and shapes. For small and low-dimensional systems the surface plasmon resonances affect the frequency of the collective excitation and position of the satellites.« less

Searches for 3.5 keV Absorption Features in Cluster AGN Spectra

NASA Astrophysics Data System (ADS)

Conlon, Joseph P.

2018-06-01

We investigate possible evidence for a spectral dip around 3.5 keV in central cluster AGNs, motivated by previous results for archival Chandra observations of the Perseus cluster and the general interest in novel spectral features around 3.5 keV that may arise from dark matter physics. We use two deep Chandra observations of the Perseus and Virgo clusters that have recently been made public. In both cases, mild improvements in the fit (Δχ2 = 4.2 and Δχ2 = 2.5) are found by including such a dip at 3.5 keV into the spectrum. A comparable result (Δχ2 = 6.5) is found re-analysing archival on-axis Chandra ACIS-S observations of the centre of the Perseus cluster.

ARTS, the Atmospheric Radiative Transfer Simulator - version 2.2, the planetary toolbox edition

NASA Astrophysics Data System (ADS)

Buehler, Stefan A.; Mendrok, Jana; Eriksson, Patrick; Perrin, Agnès; Larsson, Richard; Lemke, Oliver

2018-04-01

This article describes the latest stable release (version 2.2) of the Atmospheric Radiative Transfer Simulator (ARTS), a public domain software for radiative transfer simulations in the thermal spectral range (microwave to infrared). The main feature of this release is a planetary toolbox that allows simulations for the planets Venus, Mars, and Jupiter, in addition to Earth. This required considerable model adaptations, most notably in the area of gaseous absorption calculations. Other new features are also described, notably radio link budgets (including the effect of Faraday rotation that changes the polarization state) and the treatment of Zeeman splitting for oxygen spectral lines. The latter is relevant, for example, for the various operational microwave satellite temperature sensors of the Advanced Microwave Sounding Unit (AMSU) family.

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.

Shuttle-based measurements: GLO ultraviolet earthlimb view

NASA Astrophysics Data System (ADS)

Gardner, James A.; Murad, Edmond; Viereck, Rodney A.; Knecht, David J.; Pike, Charles P.; Broadfoot, A. Lyle

1996-11-01

The GLO experiment is an on-going shuttle-based spectrograph/imager project that has returned ultraviolet (100 - 400 nm) limb views. High spectral (0.35 nm FWHM) and temporal (4 s) resolution spectra include simultaneous altitude profiles (in the range of 80 - 400 km tangent height with 10 km resolution) of dayglow and nightglow features. Measured emissions include the NO gamma, N2 Vegard-Kaplan and second positive, N2+ first negative, and O2 Herzberg I band systems and both atomic and cation lines of N, O, and Mg. This data represents a low solar activity benchmark for future observations. We report on the status of the GLO project, which included three space flights in 1995, and present spectral data on important ultraviolet band systems.

Spectacle and SpecViz: New Spectral Analysis and Visualization Tools

NASA Astrophysics Data System (ADS)

Earl, Nicholas; Peeples, Molly; JDADF Developers

2018-01-01

A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user-created plugins that add new functionality.This work was supported in part by HST AR #13919, HST GO #14268, and HST AR #14560.

CHARA/FLUOR updates and performance

NASA Astrophysics Data System (ADS)

Mérand, Antoine; Coudé du Foresto, Vincent; Kellerer, Aglaé; ten Brummelaar, Theo; Reess, Jean-Michel; Ziegler, Denis

2006-06-01

In 2002, the Fiber Linked Unit for Optical Recombination (FLUOR) has been moved from the Infrared Optical Telescope Array (IOTA) to the CHARA Array. We present here the main upgrades that followed the installation, the new features installed, including spectral dispersion, and the current capabilities of the instrument.

Classification of ion mobility spectra by functional groups using neural networks

NASA Technical Reports Server (NTRS)

Bell, S.; Nazarov, E.; Wang, Y. F.; Eiceman, G. A.

1999-01-01

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

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.

Observations of J002E3: Possible Discovery of an Apollo Rocket Body

NASA Astrophysics Data System (ADS)

Jorgensen, K.; Rivkin, A.; Binzel, R.; Whitely, R.; Hergenrother, C.; Chodas, P.; Chesley, S.; Vilas, F.

2003-05-01

In early September 2002, spectral and photometric observations of J002E3 were made at IRTF and Mt. Biglow in an effort to determine whether the object was an asteroid or a human-made. Early observations yielded a possible spin-rate and orientation. Additional spectral observations were completed in May 2003 at the Air Force Maui Optical Supercomputing (AMOS) site. Through the modeling of common spacecraft materials, the observations of J002E3 show a strong correlation of absorption features to a combination of human-made materials including white paint, black paint, and aluminum. Absorption features in the near IR show a strong correlation with paint containing a titanium-oxide semiconductor. Using the material model and the orbital information, it was concluded that J002E3 is a human-made object from an Apollo rocket upperstage, most likely Apollo 12. In addition, the J002E3 observations were compared to spectral observations of other rocket bodies launched during a similar time and the results agree well. Results from the observations and modeling will be presented. This work has been a collaboration of governmental agencies, education institutions, and amateur astronomers. Funding agencies include National Research Council, NASA JSC, MIT, University of Arizona, and JPL.

Humor drawings evoked temporal and spectral EEG processes

PubMed Central

Kuo, Hsien-Chu; Chuang, Shang-Wen

2017-01-01

Abstract The study aimed to explore the humor processing elicited through the manipulation of artistic drawings. Using the Comprehension–Elaboration Theory of humor as the main research background, the experiment manipulated the head portraits of celebrities based on the independent variables of facial deformation (large/small) and addition of affective features (positive/negative). A 64-channel electroencephalography was recorded in 30 participants while viewing the incongruous drawings of celebrities. The electroencephalography temporal and spectral responses were measured during the three stages of humor which included incongruity detection, incongruity comprehension and elaboration of humor. Analysis of event-related potentials indicated that for humorous vs non-humorous drawings, facial deformation and the addition of affective features significantly affected the degree of humor elicited, specifically: large > small deformation; negative > positive affective features. The N170, N270, N400, N600-800 and N900-1200 components showed significant differences, particularly in the right prefrontal and frontal regions. Analysis of event-related spectral perturbation showed significant differences in the theta band evoked in the anterior cingulate cortex, parietal region and posterior cingulate cortex; and in the alpha and beta bands in the motor areas. These regions are involved in emotional processing, memory retrieval, and laughter and feelings of amusement induced by elaboration of the situation. PMID:28402573

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.

Phosphorus K-edge XANES spectroscopy of mineral standards

PubMed Central

Ingall, Ellery D.; Brandes, Jay A.; Diaz, Julia M.; de Jonge, Martin D.; Paterson, David; McNulty, Ian; Elliott, W. Crawford; Northrup, Paul

2011-01-01

Phosphorus K-edge X-ray absorption near-edge structure (XANES) spectroscopy was performed on phosphate mineral specimens including (a) twelve specimens from the apatite group covering a range of compositional variation and crystallinity; (b) six non-apatite calcium-rich phosphate minerals; (c) 15 aluminium-rich phosphate minerals; (d) ten phosphate minerals rich in either reduced iron or manganese; (e) four phosphate minerals rich in either oxidized iron or manganese; (f) eight phosphate minerals rich in either magnesium, copper, lead, zinc or rare-earth elements; and (g) four uranium phosphate minerals. The identity of all minerals examined in this study was independently confirmed using X-ray powder diffraction. Minerals were distinguished using XANES spectra with a combination of pre-edge features, edge position, peak shapes and post-edge features. Shared spectral features were observed in minerals with compositions dominated by the same specific cation. Analyses of apatite-group minerals indicate that XANES spectral patterns are not strongly affected by variations in composition and crystallinity typical of natural mineral specimens. PMID:21335905

Spectral EEG Features of a Short Psycho-physiological Relaxation

NASA Astrophysics Data System (ADS)

Teplan, Michal; Krakovská, Anna; Špajdel, Marián

2014-08-01

Short-lasting psycho-physiological relaxation was investigated through an analysis of its bipolar electroencephalographic (EEG) characteristics. In 8 subjects, 6-channel EEG data of 3-minute duration were recorded during 88 relaxation sessions. Time course of spectral EEG features was examined. Alpha powers were decreasing during resting conditions of 3-minute sessions in lying position with eyes closed. This was followed by a decrease of total power in centro-parietal cortex regions and an increase of beta power in fronto-central areas. Represented by EEG coherences the interhemispheric communication between the parieto-occipital regions was enhanced within a frequency range of 2-10 Hz. In order to discern between higher and lower levels of relaxation distinguished according to self-rated satisfaction, EEG features were assessed and discriminating parameters were identified. Successful relaxation was determined mainly by the presence of decreased delta-1 power across the cortex. Potential applications for these findings include the clinical, pharmacological, and stress management fields.

[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.

Supporting the Growing Needs of the GIS Industry

NASA Technical Reports Server (NTRS)

2003-01-01

Visual Learning Systems, Inc. (VLS), of Missoula, Montana, has developed a commercial software application called Feature Analyst. Feature Analyst was conceived under a Small Business Innovation Research (SBIR) contract with NASA's Stennis Space Center, and through the Montana State University TechLink Center, an organization funded by NASA and the U.S. Department of Defense to link regional companies with Federal laboratories for joint research and technology transfer. The software provides a paradigm shift to automated feature extraction, as it utilizes spectral, spatial, temporal, and ancillary information to model the feature extraction process; presents the ability to remove clutter; incorporates advanced machine learning techniques to supply unparalleled levels of accuracy; and includes an exceedingly simple interface for feature extraction.

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.

Using non-invasive molecular spectroscopic techniques to detect unique aspects of protein Amide functional groups and chemical properties of modeled forage from different sourced-origins

NASA Astrophysics Data System (ADS)

Ji, Cuiying; Zhang, Xuewei; Yu, Peiqiang

2016-03-01

The non-invasive molecular spectroscopic technique-FT/IR is capable to detect the molecular structure spectral features that are associated with biological, nutritional and biodegradation functions. However, to date, few researches have been conducted to use these non-invasive molecular spectroscopic techniques to study forage internal protein structures associated with biodegradation and biological functions. The objectives of this study were to detect unique aspects and association of protein Amide functional groups in terms of protein Amide I and II spectral profiles and chemical properties in the alfalfa forage (Medicago sativa L.) from different sourced-origins. In this study, alfalfa hay with two different origins was used as modeled forage for molecular structure and chemical property study. In each forage origin, five to seven sources were analyzed. The molecular spectral profiles were determined using FT/IR non-invasive molecular spectroscopy. The parameters of protein spectral profiles included functional groups of Amide I, Amide II and Amide I to II ratio. The results show that the modeled forage Amide I and Amide II were centered at 1653 cm- 1 and 1545 cm- 1, respectively. The Amide I spectral height and area intensities were from 0.02 to 0.03 and 2.67 to 3.36 AI, respectively. The Amide II spectral height and area intensities were from 0.01 to 0.02 and 0.71 to 0.93 AI, respectively. The Amide I to II spectral peak height and area ratios were from 1.86 to 1.88 and 3.68 to 3.79, respectively. Our results show that the non-invasive molecular spectroscopic techniques are capable to detect forage internal protein structure features which are associated with forage chemical properties.

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.

Reflecting Schmidt/Littrow Prism Imaging Spectrometer

NASA Technical Reports Server (NTRS)

Breckinridge, J. B.; Page, N. A.; Shack, R. V.; Shannon, R. R.

1985-01-01

High resolution achieved with wide field of view. Imaging Spectrometer features off-axis reflecting optics, including reflecting "slit" that also serves as field flattener. Only refracting element is prism. By scanning slit across object or scene and timing out signal, both spectral and spatial information in scene are obtained.

Airborne imaging spectrometer data of the Ruby Mountains, Montana: Mineral discrimination using relative absorption band-depth images

USGS Publications Warehouse

Crowley, J.K.; Brickey, D.W.; Rowan, L.C.

1989-01-01

Airborne imaging spectrometer data collected in the near-infrared (1.2-2.4 ??m) wavelength range were used to study the spectral expression of metamorphic minerals and rocks in the Ruby Mountains of southwestern Montana. The data were analyzed by using a new data enhancement procedure-the construction of relative absorption band-depth (RBD) images. RBD images, like bandratio images, are designed to detect diagnostic mineral absorption features, while minimizing reflectance variations related to topographic slope and albedo differences. To produce an RBD image, several data channels near an absorption band shoulder are summed and then divided by the sum of several channels located near the band minimum. RBD images are both highly specific and sensitive to the presence of particular mineral absorption features. Further, the technique does not distort or subdue spectral features as sometimes occurs when using other data normalization methods. By using RBD images, a number of rock and soil units were distinguished in the Ruby Mountains including weathered quartz - feldspar pegmatites, marbles of several compositions, and soils developed over poorly exposed mica schists. The RBD technique is especially well suited for detecting weak near-infrared spectral features produced by soils, which may permit improved mapping of subtle lithologic and structural details in semiarid terrains. The observation of soils rich in talc, an important industrial commodity in the study area, also indicates that RBD images may be useful for mineral exploration. ?? 1989.

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.

Near-infrared spectroscopy of primitive solar system objects

NASA Technical Reports Server (NTRS)

Luu, Jane; Jewitt, David; Cloutis, Edward

1994-01-01

We have obtained near-infrared (H and K band at lambda/Delta(lambda) is approximately 480 to 600) spectra of a sample of primitive objects including 2 Centaur objects (2060 Chiron and 5145 Pholus) and 16 P- and D-type asteroids. The spectra were obtained at the United Kingdom Infrared Telescope using the cooled grating spectrometer CGS4, and were used to search for chemically diagnostic vibrational features in these primitive objects. Pholus exhibits broad adsorption features at 2.07 and 2.27 micrometers, as well as a weak feature at 1.72 micrometers. The 1.72- and 2.27-micrometer features are similar to those seen in a laboratory tar sand sample. No distinct absorption features are found in other objects, including Chiron, which displays a spectrally neutral continuum. A comparison of the P- and D-type asteroid spectra with laboratory measurements of organic solids shows no compelling evidence for hydrocarbon overtones seen in terrestrial bituminous tar sands.

Calibration data Analysis Package (CAP): An IDL based widget application for analysis of X-ray calibration data

NASA Astrophysics Data System (ADS)

Vaishali, S.; Narendranath, S.; Sreekumar, P.

An IDL (interactive data language) based widget application developed for the calibration of C1XS (Narendranath et al., 2010) instrument on Chandrayaan-1 is modified to provide a generic package for the analysis of data from x-ray detectors. The package supports files in ascii as well as FITS format. Data can be fitted with a list of inbuilt functions to derive the spectral redistribution function (SRF). We have incorporated functions such as `HYPERMET' (Philips & Marlow 1976) including non Gaussian components in the SRF such as low energy tail, low energy shelf and escape peak. In addition users can incorporate additional models which may be required to model detector specific features. Spectral fits use a routine `mpfit' which uses Leven-Marquardt least squares fitting method. The SRF derived from this tool can be fed into an accompanying program to generate a redistribution matrix file (RMF) compatible with the X-ray spectral analysis package XSPEC. The tool provides a user friendly interface of help to beginners and also provides transparency and advanced features for experts.

Ground motion in the presence of complex Topography II: Earthquake sources and 3D simulations

USGS Publications Warehouse

Hartzell, Stephen; Ramirez-Guzman, Leonardo; Meremonte, Mark; Leeds, Alena L.

2017-01-01

Eight seismic stations were placed in a linear array with a topographic relief of 222 m over Mission Peak in the east San Francisco Bay region for a period of one year to study topographic effects. Seventy‐two well‐recorded local earthquakes are used to calculate spectral amplitude ratios relative to a reference site. A well‐defined fundamental resonance peak is observed with individual station amplitudes following the theoretically predicted progression of larger amplitudes in the upslope direction. Favored directions of vibration are also seen that are related to the trapping of shear waves within the primary ridge dimensions. Spectral peaks above the fundamental one are also related to topographic effects but follow a more complex pattern. Theoretical predictions using a 3D velocity model and accurate topography reproduce many of the general frequency and time‐domain features of the data. Shifts in spectral frequencies and amplitude differences, however, are related to deficiencies of the model and point out the importance of contributing factors, including the shear‐wave velocity under the topographic feature, near‐surface velocity gradients, and source parameters.

Quasi-continuum photoluminescence: Unusual broad spectral and temporal characteristics found in defective surfaces of silica and other materials

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

Laurence, Ted A., E-mail: laurence2@llnl.gov; Bude, Jeff D.; Shen, Nan

2014-02-28

We previously reported a novel photoluminescence (PL) with a distribution of fast decay times in fused silica surface flaws that is correlated with damage propensity by high fluence lasers. The source of the PL was not attributable to any known silica point defect. Due to its broad spectral and temporal features, we here give this PL the name quasi-continuum PL (QC-PL) and describe the features of QC-PL in more detail. The primary features of QC-PL include broad excitation and emission spectra, a broad distribution of PL lifetimes from 20 ps to 5 ns, continuous shifts in PL lifetime distributions with respectmore » to emission wavelength, and a propensity to photo-bleach and photo-brighten. We found similar PL characteristics in surface flaws of other optical materials, including CaF{sub 2}, DKDP, and quartz. Based on the commonality of the features in different optical materials and the proximity of QC-PL to surfaces, we suggest that these properties arise from interactions associated with high densities of defects, rather than a distribution over a large number of types of defects and is likely found in a wide variety of structures from nano-scale composites to bulk structures as well as in both broad and narrow band materials from dielectrics to semiconductors.« less

THE TEAM KECK REDSHIFT SURVEY 2: MOSFIRE SPECTROSCOPY OF THE GOODS-NORTH FIELD

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

Wirth, Gregory D.; Kassis, Marc; Lyke, Jim

We present the Team Keck Redshift Survey 2 (TKRS2), a near-infrared spectral observing program targeting selected galaxies within the CANDELS subsection of the GOODS-North Field. The TKRS2 program exploits the unique capabilities of the Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE), which entered service on the Keck I telescope in 2012 and contributes substantially to the study of galaxy spectral features at redshifts inaccessible to optical spectrographs. The TKRS2 project targets 97 galaxies drawn from samples that include z ≈ 2 emission-line galaxies with features observable in the JHK bands as well as lower-redshift targets with features in the Y band.more » We present a detailed measurement of MOSFIRE’s sensitivity as a function of wavelength, including the effects of telluric features across the YJHK filters. The largest utility of our survey is in providing rest-frame-optical emission lines for z > 1 galaxies, and we demonstrate that the ratios of strong, optical emission lines of z ≈ 2 galaxies suggest the presence of either higher N/O abundances than are found in z ≈ 0 galaxies or low-metallicity gas ionized by an active galactic nucleus. We have released all TKRS2 data products into the public domain to allow researchers access to representative raw and reduced MOSFIRE spectra.« less

An Interferometric Spectral Line and Imaging Survey of VY Canis Majoris in the 345 GHz Band

NASA Astrophysics Data System (ADS)

Kamiński, T.; Gottlieb, C. A.; Young, K. H.; Menten, K. M.; Patel, N. A.

2013-12-01

A spectral line survey of the oxygen-rich red supergiant VY Canis Majoris was made between 279 and 355 GHz with the Submillimeter Array (SMA). Two hundred twenty-three spectral features from 19 molecules (not counting isotopic species of some of them) were observed, including the rotational spectra of TiO, TiO2, and AlCl for the first time in this source. The parameters and an atlas of all spectral features are presented. Observations of each line with a synthesized beam of ~0.''9, reveal the complex kinematics and morphology of the nebula surrounding VY CMa. Many of the molecules are observed in high-lying rotational levels or in excited vibrational levels. From these, it was established that the main source of the submillimeter-wave continuum (dust) and the high-excitation molecular gas (the star) are separated by about 0.''15. Apparent coincidences between the molecular gas observed with the SMA, and some of the arcs and knots observed at infrared wavelengths and in the optical scattered light by the Hubble Space Telescope are identified. The observations presented here provide important constraints on the molecular chemistry in oxygen-dominated circumstellar environments and a deeper picture of the complex circumstellar environment of VY CMa.

Camouflaged target detection based on polarized spectral features

NASA Astrophysics Data System (ADS)

Tan, Jian; Zhang, Junping; Zou, Bin

2016-05-01

The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

Analytical approaches to modelling panspermia - beyond the mean-field paradigm

NASA Astrophysics Data System (ADS)

Lingam, Manasvi

2016-01-01

We model the process of panspermia by adopting two different approaches. The first method conceives it as a self-replication process, endowed with non-local creation and extinction. We show that some features suggestive of universal behaviour emerge, such as exponential decay or growth, and a power spectral density that displays a power-law behaviour in a particular regime. We also present a special case wherein the number density of the planets seeded through panspermia approaches a finite asymptotic distribution. The power spectral density for the independent and spontaneous emergence of life is investigated in conjunction with its counterpart for panspermia. The former exhibits attributes characteristic of a noise spectrum, including the resemblance to white noise in a certain regime. These features are absent in panspermia, suggesting that the power spectral density could be utilized as a future tool for differentiating between the two processes. Our second approach adopts the machinery of Markov processes and diffusion, and we show that the power spectral density exhibits a power-law tail in some domains, as earlier, suggesting that this behaviour may be fairly robust. We comment on a generalization of the diffusive model, and also indicate how the methods and results developed herein could be used to analyse other phenomena.

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.

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.

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.

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

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.

The puzzling spectrum of HD 94509. Sounding out the extremes of Be shell star spectral morphology

NASA Astrophysics Data System (ADS)

Cowley, C. R.; Przybilla, N.; Hubrig, S.

2015-06-01

Context. The spectral features of HD 94509 are highly unusual, adding an extreme to the zoo of Be and shell stars. The shell dominates the spectrum, showing lines typical for spectral types mid-A to early-F, while the presence of a late/mid B-type central star is indicated by photospheric hydrogen line wings and helium lines. Numerous metallic absorption lines have broad wings but taper to narrow cores. They cannot be fit by Voigt profiles. Aims: We describe and illustrate unusual spectral features of this star, and make rough calculations to estimate physical conditions and abundances in the shell. Furthermore, the central star is characterized. Methods: We assume mean conditions for the shell. An electron density estimate is made from the Inglis-Teller formula. Excitation temperatures and column densities for Fe i and Fe ii are derived from curves of growth. The neutral H column density is estimated from high Paschen members. The column densities are compared with calculations made with the photoionization code Cloudy. Atmospheric parameters of the central star are constrained employing non-LTE spectrum synthesis. Results: Overall chemical abundances are close to solar. Column densities of the dominant ions of several elements, as well as excitation temperatures and the mean electron density are well accounted for by a simple model. Several features, including the degree of ionization, are less well described. Conclusions: HD 94509 is a Be star with a stable shell, close to the terminal-age main sequence. The dynamical state of the shell and the unusually shaped, but symmetric line profiles, require a separate study.

VNIR spectral features observed by the Mars Exploration Rover Opportunity in hematite-bearing materials at Meridiani Planum

NASA Astrophysics Data System (ADS)

Farrand, W. H.; Bell, J. F.; Morris, R. V.; Joliff, B. L.; Squyres, S. W.; Souza, P. A.

2004-12-01

The Mars Exploration Rover Opportunity was sent to Meridiani Planum based largely on MGS TES spectroscopic evidence of a large surface exposure of coarse grained gray hematite. The presence of hematite at Meridiani Planum has been confirmed through thermal infrared spectroscopy by the rover's Mini-TES instrument and by in-situ measurements by its Moessbauer (MB) spectrometer. Several types of hematite, as expressed by differences in MB spectral parameters, have been associated with various rocks and soils examined in Eagle crater and on the surrounding plains. The host materials include the small spherules (informally known as "blueberries") littering the floor of Eagle crater and the plains of Meridiani, the outcrop rock itself, specific types of soils, and two measurements on unique rocks in the Shoemaker's Patio area of Eagle crater. At the visible to near infrared (VNIR) wavelengths covered by the rover's multispectral Panoramic camera (Pancam), gray hematite is spectrally neutral. However, multispectral observations by Pancam of some of these hematite-bearing materials show discernable spectral features. Specifically, portions of the outcrop visible in the walls of Eagle crater display a strong 535 nm absorption feature. This feature resembles a similar feature in laboratory spectra of red hematite, but the characteristic 860 nm absorption of red hematite is either absent or is instead replaced by a longer wavelength absorption centered on Pancam's 900 nm channel. The blueberries display a deep and broad absorption centered on 900 nm and as well as an increase in reflectance in the 1009 nm band. The shape of the absorption feature in the blueberries is consistent with that seen in red hematite, but again the band minimum is displaced to a longer wavelength than would be expected for red hematite. The blueberries also lack the prominent absorption at the shortest wavelengths that would be expected of red hematite. The unique hematite-bearing (or coated) rocks at Shoemaker's Patio lack the very strong 535 nm band depth of other portions of the outcrop but still have a stronger 535 nm feature than most of the outcrop. Interestingly, VNIR spectra more consistent with that expected for red hematite have been found in cuttings released by grinding into outcrop by the rover's Rock Abrasion Tool. The cause of the observed spectral features in the portions of outcrop with strong 535 nm band depths and of the reddish rocks in the Shoemaker's Patio area is believed to be attributable either to red hematite mixed with other Fe3+ - bearing phases (such as jarosite and/or schwertmannite) or, at the longer wavelengths, with Fe2+ - bearing phases (such as pyroxenes). Determination of the nature of these iron-bearing materials will further elucidate the geologic, aqueous and diagenetic history of the rocks at Meridiani Planum.

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.

Compositional Analyses and Implications of Visible/Near-Infrared Spectra of Outer Irregular Jovian Satellites

NASA Astrophysics Data System (ADS)

Vilas, Faith; Hendrix, Amanda

2017-10-01

The existence of a visible-near infrared absorption feature attributed to aqueous alteration products has been suggested in both grey and reddened broadband photometry of some outer irregular jovian satellites. Moderate resolution VNIR narrowband spectroscopy was obtained of the jovian irregular satellites JVI Himalia, JVII Elara, JVIII Pasiphae, JIX Sinope, JX Lysithea, JXI Carme, JXII Ananke and JXVII Callirrhoe in 2006, 2008, 2009, and 2010 using the MMT Observatory facility Red Channel spectrograph to confirm the presence of this feature. The spectra are centered near 0.64 μm in order to cover the 0.7-μm feature entirely (generally ranging from 0.57 to 0.83 μm). The spectra generally have a dispersion/element of ~0.6 nm (6Å) some spectra are smoothed. These spectra sample three prograde (i = 28o), four retrograde (i = 149o, 165o) and one independent satellite.We observe these findings among the spectra:- An absorption feature centered near 0.7 µm exists in the spectra of the three prograde (i = 28o) satellites. This feature is spectrally broader than the 0.7-µm feature observed in C-complex asteroids. None appears spectrally reddened. This suggests that these prograde satellites have a common parent body.- A different absorption feature appears in the spectra of the three retrograde (i = 149o) satellites, also suggesting a common parent body. Varying reddening is observed. This feature is similar in spectral location and width to the 0.7-µm feature.- Reddening is observed in the individual observation of JXI Carme (i = 165o), and independent satellite JIX Sinope, similar to the D-class asteroid spectra dominating the Trojan population. A suggested absorption feature is being investigated.Mixing modeling of combinations of both expected and proposed compositions including carbonaceous materials, phyllosilicates, mafic silicates, and other opaque materials, is currently underway. Results will be reported and discussed at the meeting.Acknowledgments: The MMT Observatory is a joint facility of the University of Arizona and the Smithsonian Institution. This research has been supported by SSERVI CLASS.

Spectral characteristics of iron-bearing phyllosilicates: Comparison to Orgueil (CI1), Murchison and Murray (CM2)

USGS Publications Warehouse

Calvin, W.M.; King, T.V.V.

1997-01-01

Phyllosilicate alteration minerals are commonly found in low petrologic types of carbonaceous chondrites. Previous spectral studies have examined Mg-bearing phyllosilicates with limited success in matching the spectral properties of CM and CI chondrites. Transmission electron microscope and other analytical techniques suggest that Fe-bearing clays are more abundant in CI and CM chondrites than magnesian varieties. Here, we present the results of an examination of the reflectance spectra of Fe-phyllosilicates, including serpentines and berthierines, of which the latter were formerly known as septechlorites. We have measured the diffuse reflectance spectra of powdered samples from 0.3 to 25 ??m. We find that these minerals provide a better spectral match to many of the features seen in CI and CM chondrites, and simple linear combinations of the spectra of both Fe- and Mg-phyllosilicates closely approximate the spectra of CM and CI chondrites.

Constraining the Star-Formation and Metal-Enrichment Histories of Galaxies with the Next Generation Spectral Library

NASA Astrophysics Data System (ADS)

Heap, Sara

2009-07-01

Hubble's Next Generation Spectral Library {NGSL} comprises intermediate-resolution {R 1000} STIS spectra of 378 stars having a wide range in metallicity and age. Unique features of the NGSL include its broad wavelength coverage {1,800-10,100 ?} and high-S/N, absolute spectrophotometry. When incorporated in modern stellar population synthesis codes, the NGSL should enable us to constrain simultaneously the star-formation history and metal-enrichment history of galaxies over a wide redshift interval {z= 0-2}. In AR10659, we laid the foundation for tracing the spectral evolution of galaxies by putting the NGSL in order. We now propose to derive the atmospheric and fundamental parameters of the program stars, generate integrated spectra of stellar populations of different metallicities and initial mass functions, and derive spectral diagnostics of the age, metalllicity and E{B-V} of stellar populations.

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...

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).

Systems and methods for selective detection and imaging in coherent Raman microscopy by spectral excitation shaping

DOEpatents

Xie, Xiaoliang Sunney; Freudiger, Christian; Min, Wei

2016-03-15

A microscopy imaging system is disclosed that includes a light source system, a spectral shaper, a modulator system, an optics system, an optical detector and a processor. The light source system is for providing a first train of pulses and a second train of pulses. The spectral shaper is for spectrally modifying an optical property of at least some frequency components of the broadband range of frequency components such that the broadband range of frequency components is shaped producing a shaped first train of pulses to specifically probe a spectral feature of interest from a sample, and to reduce information from features that are not of interest from the sample. The modulator system is for modulating a property of at least one of the shaped first train of pulses and the second train of pulses at a modulation frequency. The optical detector is for detecting an integrated intensity of substantially all optical frequency components of a train of pulses of interest transmitted or reflected through the common focal volume. The processor is for detecting a modulation at the modulation frequency of the integrated intensity of substantially all of the optical frequency components of the train of pulses of interest due to the non-linear interaction of the shaped first train of pulses with the second train of pulses as modulated in the common focal volume, and for providing an output signal for a pixel of an image for the microscopy imaging system.

A Tape Method for Fast Characterization and Identification of Active Pharmaceutical Ingredients in the 2-18 THz Spectral Range

NASA Astrophysics Data System (ADS)

Kissi, Eric Ofosu; Bawuah, Prince; Silfsten, Pertti; Peiponen, Kai-Erik

2015-03-01

In order to find counterfeit drugs quickly and reliably, we have developed `tape method' a transmission spectroscopic terahertz (THz) measurement technique and compared it with a standard attenuated total reflection (ATR) THz spectroscopic measurement. We used well-known training samples, which include commercial paracetamol and aspirin tablets to check the validity of these two measurement techniques. In this study, the spectral features of some active pharmaceutical ingredients (APIs), such as aspirin and paracetamol are characterized for identification purpose. This work covers a wide THz spectral range namely, 2-18 THz. This proposed simple but novel technique, the tape method, was used for characterizing API and identifying their presence in their dosage forms. By comparing the spectra of the APIs to their dosage forms (powder samples), all distinct fingerprints present in the APIs are also present in their respective dosage forms. The positions of the spectral features obtained with the ATR techniques were akin to that obtained from the tape method. The ATR and the tape method therefore, complement each other. The presence of distinct fingerprints in this spectral range has highlighted the possibility of developing fast THz sensors for the screening of pharmaceuticals. It is worth noting that, the ATR method is applicable to flat faced tablets whereas the tape method is suitable for powders in general (e.g. curved surface tablets that require milling before measurement). Finally, we have demonstrated that ATR techniques can be used to screen counterfeit antimalarial tablets.

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.

Indications of the Mineralogy of Callisto and Mars from Reflectance Spectroscopy.

NASA Astrophysics Data System (ADS)

Calvin, Wendy Marie

1991-02-01

Remotely sensed reflectance spectra contain information on mineral identities, grain sizes, and abundances. This thesis consists of analysis of such spectra for two planetary objects, Callisto and Mars. Theoretical modeling of telescopic spectra of Callisto indicates that the surface consists of 20 to 45 wt% water ice at large grain sizes. In the spectral region beyond 3 μm absorption by hydrated mineral phases is dominant. The non-ice material is spectrally similar to hydrous alteration minerals that are commonly found in certain petrologic types of meteorites. New high-resolution data of Callisto are consistent with the findings of the modeling study. In addition, these new data have identified the presence of a small amount of fine-grained water ice on the leading hemisphere, through a characteristic absorption near 3.4 mum. Variations in the depth of this absorption feature indicate dynamic competition between processes which create and erode fine -grained water ice. Calibration and analysis of spectrometer data from the Mariner 6 and 7 space-craft has provided new information regarding the mineralogy of Mars. Laboratory measurements and theoretical calculations of CO_2 frosts have allowed an analysis of spectra taken over the martian south polar cap. The grain sizes in the seasonal cap are quite large and there may be evidence of contamination by water frost or dust. Analysis of Mariner spectra in non-polar regions have tentatively identified absorption features near 2.76 μm and 5.4 mum. The location of these features, and other absorptions identified from terrestrial observations, are consistent with the spectra of hydrous magnesium carbonates. The hydrous carbonates do not have strong spectral features typically associated with carbonates. Theoretical calculations of mixtures indicates that 10-30wt% of these minerals can be included and still be consistent with spectral observations. These minerals form on earth through weathering of mafic minerals with the production of amorphous iron oxides as byproducts, consistent with both present and inferred past martian environments. The presence of hydrous carbonates can provide a mechanism for having abundant carbonates on Mars while spectral searches for (anhydrous) carbonates will not find any evidence for them.

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.

Composite multilobe descriptors for cross-spectral recognition of full and partial face

NASA Astrophysics Data System (ADS)

Cao, Zhicheng; Schmid, Natalia A.; Bourlai, Thirimachos

2016-08-01

Cross-spectral image matching is a challenging research problem motivated by various applications, including surveillance, security, and identity management in general. An example of this problem includes cross-spectral matching of active infrared (IR) or thermal IR face images against a dataset of visible light images. A summary of recent developments in the field of cross-spectral face recognition by the authors is presented. In particular, it describes the original form and two variants of a local operator named composite multilobe descriptor (CMLD) for facial feature extraction with the purpose of cross-spectral matching of near-IR, short-wave IR, mid-wave IR, and long-wave IR to a gallery of visible light images. The experiments demonstrate that the variants of CMLD outperform the original CMLD and other recently developed composite operators used for comparison. In addition to different IR spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated. Performance of CMLD I to III is evaluated for each of the three cases of distances. The newly developed operators, CMLD I to III, are further utilized to conduct a study on cross-spectral partial face recognition where different facial regions are compared in terms of the amount of useful information they contain for the purpose of conducting cross-spectral face recognition. The experimental results show that among three facial regions considered in the experiments the eye region is the most informative for all IR spectra at all standoff distances.

Smile effect detection for dispersive hypersepctral imager based on the doped reflectance panel

NASA Astrophysics Data System (ADS)

Zhou, Jiankang; Liu, Xiaoli; Ji, Yiqun; Chen, Yuheng; Shen, Weimin

2012-11-01

Hyperspectral imager is now widely used in many regions, such as resource development, environmental monitoring and so on. The reliability of spectral data is based on the instrument calibration. The smile, wavelengths at the center pixels of imaging spectrometer detector array are different from the marginal pixels, is a main factor in the spectral calibration because it can deteriorate the spectral data accuracy. When the spectral resolution is high, little smile can result in obvious signal deviation near weak atmospheric absorption peak. The traditional method of detecting smile is monochromator wavelength scanning which is time consuming and complex and can not be used in the field or at the flying platform. We present a new smile detection method based on the holmium oxide panel which has the rich of absorbed spectral features. The higher spectral resolution spectrometer and the under-test imaging spectrometer acquired the optical signal from the Spectralon panel and the holmium oxide panel respectively. The wavelength absorption peak positions of column pixels are determined by curve fitting method which includes spectral response function sequence model and spectral resampling. The iteration strategy and Pearson coefficient together are used to confirm the correlation between the measured and modeled spectral curve. The present smile detection method is posed on our designed imaging spectrometer and the result shows that it can satisfy precise smile detection requirement of high spectral resolution imaging spectrometer.

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

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.

A framework for evaluating mixture analysis algorithms

NASA Astrophysics Data System (ADS)

Dasaratha, Sridhar; Vignesh, T. S.; Shanmukh, Sarat; Yarra, Malathi; Botonjic-Sehic, Edita; Grassi, James; Boudries, Hacene; Freeman, Ivan; Lee, Young K.; Sutherland, Scott

2010-04-01

In recent years, several sensing devices capable of identifying unknown chemical and biological substances have been commercialized. The success of these devices in analyzing real world samples is dependent on the ability of the on-board identification algorithm to de-convolve spectra of substances that are mixtures. To develop effective de-convolution algorithms, it is critical to characterize the relationship between the spectral features of a substance and its probability of detection within a mixture, as these features may be similar to or overlap with other substances in the mixture and in the library. While it has been recognized that these aspects pose challenges to mixture analysis, a systematic effort to quantify spectral characteristics and their impact, is generally lacking. In this paper, we propose metrics that can be used to quantify these spectral features. Some of these metrics, such as a modification of variance inflation factor, are derived from classical statistical measures used in regression diagnostics. We demonstrate that these metrics can be correlated to the accuracy of the substance's identification in a mixture. We also develop a framework for characterizing mixture analysis algorithms, using these metrics. Experimental results are then provided to show the application of this framework to the evaluation of various algorithms, including one that has been developed for a commercial device. The illustration is based on synthetic mixtures that are created from pure component Raman spectra measured on a portable device.

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.

Interferometric atmospheric refractive-index environmental monitor

NASA Astrophysics Data System (ADS)

Ludman, Jacques E.; Ludman, Jacques J.; Callahan, Heidi; Robinson, John; Davis, Seth; Caulfield, H. John; Watt, David; Sampson, John L.; Hunt, Arlon

1995-06-01

Long, open-path, outdoor interferometric measurement of the index of refraction as a function of wavelength (spectral refractivity) requires a number of innovations. These include active compensation for vibration and turbulence. The use of electronic compensation produces an electronic signal that is ideal for extracting data. This allows the appropriate interpretation of those data and the systematic and fast scanning of the spectrum by the use of bandwidths that are intermediate between lasers (narrow bandwidth) and white light (broad bandwidth). An Environmental Interferometer that incorporates these features should be extremely valuable in both pollutant detection and pollutant identification. Spectral refractivity measurements complement the information available

Gallium arsenide (GaAs) (001) after sublimation of arsenic (As) thin-film cap, by XPS

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

Engelhard, Mark H.; Lyubinetsky, Andre; Baer, Don R.

2016-12-01

Survey and high energy resolution spectra are reported for MBE grown GaAs (001) that had been capped with As. The As cap was removed by heating in situ prior to analysis. The current data expands upon the spectral regions previously reported in Surface Science Spectra. High energy resolution spectral features reported include: 2p, 3s, 3p, 3d, and L3M45M45 peaks for As; 2p, 3s, 3p, 3d, and L3M45M45 peaks for Ga; and the valance band region.

Systems and methods for analyzing building operations sensor data

DOEpatents

Mezic, Igor; Eisenhower, Bryan A.

2015-05-26

Systems and methods are disclosed for analyzing building sensor information and decomposing the information therein to a more manageable and more useful form. Certain embodiments integrate energy-based and spectral-based analysis methods with parameter sampling and uncertainty/sensitivity analysis to achieve a more comprehensive perspective of building behavior. The results of this analysis may be presented to a user via a plurality of visualizations and/or used to automatically adjust certain building operations. In certain embodiments, advanced spectral techniques, including Koopman-based operations, are employed to discern features from the collected building sensor data.

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.

Spectral Analysis of Breast Cancer on Tissue Microarrays: Seeing Beyond Morphology

DTIC Science & Technology

2005-04-01

Harvey N., Szymanski J.J., Bloch J.J., Mitchell M. investigation of image feature extraction by a genetic algorithm. Proc. SPIE 1999;3812:24-31. 11...automated feature extraction using multiple data sources. Proc. SPIE 2003;5099:190-200. 15 4 Spectral-Spatial Analysis of Urine Cytology Angeletti et al...Appendix Contents: 1. Harvey, N.R., Levenson, R.M., Rimm, D.L. (2003) Investigation of Automated Feature Extraction Techniques for Applications in

Complex refractive index measurements for BaF 2 and CaF 2 via single-angle infrared reflectance spectroscopy

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

Kelly-Gorham, Molly Rose K.; DeVetter, Brent M.; Brauer, Carolyn S.

We have re-investigated the optical constants n and k for the homologous series of inorganic salts barium fluoride (BaF2) and calcium fluoride (CaF2) using a single-angle near-normal incidence reflectance device in combination with a calibrated Fourier transform infrared (FTIR) spectrometer. Our results are in good qualitative agreement with most previous works. However, certain features of the previously published data near the reststrahlen band exhibit distinct differences in spectral characteristics. Notably, our measurements of BaF2 do not include a spectral feature in the ~250 cm-1 reststrahlen band that was previously published. Additionally, CaF2 exhibits a distinct wavelength shift relative to themore » model derived from previously published data. We confirmed our results with recently published works that use significantly more modern instrumentation and data reduction techniques« less

Response comment: Carbon sequestration on Mars

USGS Publications Warehouse

Edwards, Christopher; Ehlmann, Bethany L.

2016-01-01

Martian atmospheric pressure has important implications for the past and present habitability of the planet, including the timing and causes of environmental change. The ancient Martian surface is strewn with evidence for early water bound in minerals (e.g., Ehlmann and Edwards, 2014) and recorded in surface features such as large catastrophically created outflow channels (e.g., Carr, 1979), valley networks (Hynek et al., 2010; Irwin et al., 2005), and crater lakes (e.g., Fassett and Head, 2008). Using orbital spectral data sets coupled with geologic maps and a set of numerical spectral analysis models, Edwards and Ehlmann (2015) constrained the amount of atmospheric sequestration in early Martian rocks and found that the majority of this sequestration occurred prior to the formation of the early Hesperian/late Noachian valley networks (Fassett and Head, 2011; Hynek et al., 2010), thus implying the atmosphere was already thin by the time these surface-water-related features were formed.

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.

Sports Stars: Analyzing the Performance of Astronomers at Visualization-based Discovery

NASA Astrophysics Data System (ADS)

Fluke, C. J.; Parrington, L.; Hegarty, S.; MacMahon, C.; Morgan, S.; Hassan, A. H.; Kilborn, V. A.

2017-05-01

In this data-rich era of astronomy, there is a growing reliance on automated techniques to discover new knowledge. The role of the astronomer may change from being a discoverer to being a confirmer. But what do astronomers actually look at when they distinguish between “sources” and “noise?” What are the differences between novice and expert astronomers when it comes to visual-based discovery? Can we identify elite talent or coach astronomers to maximize their potential for discovery? By looking to the field of sports performance analysis, we consider an established, domain-wide approach, where the expertise of the viewer (i.e., a member of the coaching team) plays a crucial role in identifying and determining the subtle features of gameplay that provide a winning advantage. As an initial case study, we investigate whether the SportsCode performance analysis software can be used to understand and document how an experienced Hi astronomer makes discoveries in spectral data cubes. We find that the process of timeline-based coding can be applied to spectral cube data by mapping spectral channels to frames within a movie. SportsCode provides a range of easy to use methods for annotation, including feature-based codes and labels, text annotations associated with codes, and image-based drawing. The outputs, including instance movies that are uniquely associated with coded events, provide the basis for a training program or team-based analysis that could be used in unison with discipline specific analysis software. In this coordinated approach to visualization and analysis, SportsCode can act as a visual notebook, recording the insight and decisions in partnership with established analysis methods. Alternatively, in situ annotation and coding of features would be a valuable addition to existing and future visualization and analysis packages.

Audio Spectrogram Representations for Processing with Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Wyse, L.

2017-05-01

One of the decisions that arise when designing a neural network for any application is how the data should be represented in order to be presented to, and possibly generated by, a neural network. For audio, the choice is less obvious than it seems to be for visual images, and a variety of representations have been used for different applications including the raw digitized sample stream, hand-crafted features, machine discovered features, MFCCs and variants that include deltas, and a variety of spectral representations. This paper reviews some of these representations and issues that arise, focusing particularly on spectrograms for generating audio using neural networks for style transfer.

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.

A synthetic high fidelity, high cadence spectral Earth database

NASA Astrophysics Data System (ADS)

Schwieterman, Edward; Meadows, Victoria; Robinson, Tyler D.; Lustig-Yaeger, Jacob; Sparks, William B.; Cracraft, Misty

2016-10-01

Earth is currently our only, and will always be our best, example of a living planet. While Earth data model comparisons have been effectively used in recent years to validate spectral models, observations by interplanetary spacecraft are limited to "snapshots" in terms of viewing geometry and Earth's dynamic surface and atmosphere state. We use the well-validated Virtual Planetary Laboratory 3D spectral Earth model to generate both simulated disk-averaged spectra and high resolution, spatially resolved spectral data cubes of Earth at a viewing geometry consistent with Lunar viewing angles at wavelengths from the far UV (0.1 μm) the to the far IR (200 μm). The database includes disk-averaged spectra from dates 03/19/2008 to 04/23/2008 at one-hour cadence and fully spectral data cubes for a subset of those times. These spectral products have a wide range of applications including calibration of spacecraft instrumentation (Robinson et al. 2014), modeling the radiation environment of permanently shadowed Lunar craters due to Earthshine (Glenar et al., in prep), and testing the detectability of atmospheric and surface features of an Earth-like planet orbiting a distant star with a large space-based telescope mission concepts such as LUVOIR. These data include the phase and time-dependent changes in spectral biosignatures (O2, O3, CH4, VRE) and habitability markers (N2, H2O, CO2, ocean glint). The advantages of the VPL Earth model data products over 1D spectra traditionally used for testing instrument architectures include accurate modeling of Earth's surface inhomogeneity (continental distribution and ice caps), cloud cover and variability, pole to equator temperature gradients, obliquity, phase-dependent scattering effects, and rotation. We present a subset of this spectral data including anticipated signal-to-noise calculations of an exoEarth twin at different phases using a coronagraph instrument model (Robinson et al. 2015). We also calculate time-dependent UBVRIJHK absolute magnitudes of Earth and binned intensities (W m-2 sr-1) in wavelength ranges (0.4-1 μm, 0.2-2 μm, 5-25 μm, and > 10 μm) relevant for planet detection with proposed space telescope missions.

An unsupervised classification approach for analysis of Landsat data to monitor land reclamation in Belmont county, Ohio

NASA Technical Reports Server (NTRS)

Brumfield, J. O.; Bloemer, H. H. L.; Campbell, W. J.

1981-01-01

Two unsupervised classification procedures for analyzing Landsat data used to monitor land reclamation in a surface mining area in east central Ohio are compared for agreement with data collected from the corresponding locations on the ground. One procedure is based on a traditional unsupervised-clustering/maximum-likelihood algorithm sequence that assumes spectral groupings in the Landsat data in n-dimensional space; the other is based on a nontraditional unsupervised-clustering/canonical-transformation/clustering algorithm sequence that not only assumes spectral groupings in n-dimensional space but also includes an additional feature-extraction technique. It is found that the nontraditional procedure provides an appreciable improvement in spectral groupings and apparently increases the level of accuracy in the classification of land cover categories.

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.

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.

Classification and Recognition of Tomb Information in Hyperspectral Image

NASA Astrophysics Data System (ADS)

Gu, M.; Lyu, S.; Hou, M.; Ma, S.; Gao, Z.; Bai, S.; Zhou, P.

2018-04-01

There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

Spatial variation analyses of Thematic Mapper data for the identification of linear features in agricultural landscapes

NASA Technical Reports Server (NTRS)

Pelletier, R. E.

1984-01-01

A need exists for digitized information pertaining to linear features such as roads, streams, water bodies and agricultural field boundaries as component parts of a data base. For many areas where this data may not yet exist or is in need of updating, these features may be extracted from remotely sensed digital data. This paper examines two approaches for identifying linear features, one utilizing raw data and the other classified data. Each approach uses a series of data enhancement procedures including derivation of standard deviation values, principal component analysis and filtering procedures using a high-pass window matrix. Just as certain bands better classify different land covers, so too do these bands exhibit high spectral contrast by which boundaries between land covers can be delineated. A few applications for this kind of data are briefly discussed, including its potential in a Universal Soil Loss Equation Model.

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.

[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).

Excitation-scanning hyperspectral imaging as a means to discriminate various tissues types

NASA Astrophysics Data System (ADS)

Deal, Joshua; Favreau, Peter F.; Lopez, Carmen; Lall, Malvika; Weber, David S.; Rich, Thomas C.; Leavesley, Silas J.

2017-02-01

Little is currently known about the fluorescence excitation spectra of disparate tissues and how these spectra change with pathological state. Current imaging diagnostic techniques have limited capacity to investigate fluorescence excitation spectral characteristics. This study utilized excitation-scanning hyperspectral imaging to perform a comprehensive assessment of fluorescence spectral signatures of various tissues. Immediately following tissue harvest, a custom inverted microscope (TE-2000, Nikon Instruments) with Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) were used to acquire hyperspectral image data from each sample. Scans utilized excitation wavelengths from 340 nm to 550 nm in 5 nm increments. Hyperspectral images were analyzed with custom Matlab scripts including linear spectral unmixing (LSU), principal component analysis (PCA), and Gaussian mixture modeling (GMM). Spectra were examined for potential characteristic features such as consistent intensity peaks at specific wavelengths or intensity ratios among significant wavelengths. The resultant spectral features were conserved among tissues of similar molecular composition. Additionally, excitation spectra appear to be a mixture of pure endmembers with commonalities across tissues of varied molecular composition, potentially identifiable through GMM. These results suggest the presence of common autofluorescent molecules in most tissues and that excitationscanning hyperspectral imaging may serve as an approach for characterizing tissue composition as well as pathologic state. Future work will test the feasibility of excitation-scanning hyperspectral imaging as a contrast mode for discriminating normal and pathological tissues.

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.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

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.

Modeling chromatic instrumental effects for a better model fitting of optical interferometric data

NASA Astrophysics Data System (ADS)

Tallon, M.; Tallon-Bosc, I.; Chesneau, O.; Dessart, L.

2014-07-01

Current interferometers often collect data simultaneously in many spectral channels by using dispersed fringes. Such polychromatic data provide powerful insights in various physical properties, where the observed objects show particular spectral features. Furthermore, one can measure spectral differential visibilities that do not directly depend on any calibration by a reference star. But such observations may be sensitive to instrumental artifacts that must be taken into account in order to fully exploit the polychromatic information of interferometric data. As a specimen, we consider here an observation of P Cygni with the VEGA visible combiner on CHARA interferometer. Indeed, although P Cygni is particularly well modeled by the radiative transfer code CMFGEN, we observe questionable discrepancies between expected and actual interferometric data. The problem is to determine their origin and disentangle possible instrumental effects from the astrophysical information. By using an expanded model fitting, which includes several instrumental features, we show that the differential visibilities are well explained by instrumental effects that could be otherwise attributed to the object. Although this approach leads to more reliable results, it assumes a fit specific to a particular instrument, and makes it more difficult to develop a generic model fitting independent of any instrument.

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

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.

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.

Complete 13C NMR chemical shifts assignment for cholesterol crystals by combined CP-MAS spectral editing and ab initio GIPAW calculations with dispersion forces.

PubMed

Küçükbenli, Emine; Sonkar, Kanchan; Sinha, Neeraj; de Gironcoli, Stefano

2012-04-12

We report here the first fully ab initio determination of (13)C NMR spectra for several crystal structures of cholesterol, observed in various biomaterials. We combine Gauge-Including Projector Augmented Waves (GIPAW) calculations at relaxed structures, fully including dispersion forces, with Magic Angle Spinning Solid State NMR experiments and spectral editing to achieve a detailed interpretation of the complex NMR spectra of cholesterol crystals. By introducing an environment-dependent secondary referencing scheme in our calculations, not only do we reproduce the characteristic spectral features of the different crystalline polymorphs, thus clearly discriminating among them, but also closely represent the spectrum in the region of several highly overlapping peaks. This, in combination with spectral editing, allows us to provide a complete peak assignment for monohydrate (ChM) and low-temperature anhydrous (ChAl) crystal polymorphs. Our results show that the synergy between ab initio calculations and refined experimental techniques can be exploited for an accurate and efficient NMR crystallography of complex systems of great interest for biomaterial studies. The method is general in nature and can be applied for studies of various complex biomaterials.

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.

Mapping the mineralogy and lithology of Canyonlands, Utah with imaging spectrometer data and the multiple spectral feature mapping algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.; Gallagher, Andrea

1992-01-01

The sedimentary sections exposed in the Canyonlands and Arches National Parks region of Utah (generally referred to as 'Canyonlands') consist of sandstones, shales, limestones, and conglomerates. Reflectance spectra of weathered surfaces of rocks from these areas show two components: (1) variations in spectrally detectable mineralogy, and (2) variations in the relative ratios of the absorption bands between minerals. Both types of information can be used together to map each major lithology and the Clark spectral features mapping algorithm is applied to do the job.

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.

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.

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

Detection of spectral line curvature in imaging spectrometer data

NASA Astrophysics Data System (ADS)

Neville, Robert A.; Sun, Lixin; Staenz, Karl

2003-09-01

A procedure has been developed to measure the band-centers and bandwidths for imaging spectrometers using data acquired by the sensor in flight. This is done for each across-track pixel, thus allowing the measurement of the instrument's slit curvature or spectral 'smile'. The procedure uses spectral features present in the at-sensor radiance which are common to all pixels in the scene. These are principally atmospheric absorption lines. The band-center and bandwidth determinations are made by correlating the sensor measured radiance with a modelled radiance, the latter calculated using MODTRAN 4.2. Measurements have been made for a number of instruments including Airborne Visible and Infra-Red Imaging Spectrometer (AVIRIS), SWIR Full Spectrum Imager (SFSI), and Hyperion. The measurements on AVIRIS data were performed as a test of the procedure; since AVIRIS is a whisk-broom scanner it is expected to be free of spectral smile. SFSI is an airborne pushbroom instrument with considerable spectral smile. Hyperion is a satellite pushbroom sensor with a relatively small degree of smile. Measurements of Hyperion were made using three different data sets to check for temporal variations.

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

Using non-invasive molecular spectroscopic techniques to detect unique aspects of protein Amide functional groups and chemical properties of modeled forage from different sourced-origins.

PubMed

Ji, Cuiying; Zhang, Xuewei; Yu, Peiqiang

2016-03-05

The non-invasive molecular spectroscopic technique-FT/IR is capable to detect the molecular structure spectral features that are associated with biological, nutritional and biodegradation functions. However, to date, few researches have been conducted to use these non-invasive molecular spectroscopic techniques to study forage internal protein structures associated with biodegradation and biological functions. The objectives of this study were to detect unique aspects and association of protein Amide functional groups in terms of protein Amide I and II spectral profiles and chemical properties in the alfalfa forage (Medicago sativa L.) from different sourced-origins. In this study, alfalfa hay with two different origins was used as modeled forage for molecular structure and chemical property study. In each forage origin, five to seven sources were analyzed. The molecular spectral profiles were determined using FT/IR non-invasive molecular spectroscopy. The parameters of protein spectral profiles included functional groups of Amide I, Amide II and Amide I to II ratio. The results show that the modeled forage Amide I and Amide II were centered at 1653 cm(-1) and 1545 cm(-1), respectively. The Amide I spectral height and area intensities were from 0.02 to 0.03 and 2.67 to 3.36 AI, respectively. The Amide II spectral height and area intensities were from 0.01 to 0.02 and 0.71 to 0.93 AI, respectively. The Amide I to II spectral peak height and area ratios were from 1.86 to 1.88 and 3.68 to 3.79, respectively. Our results show that the non-invasive molecular spectroscopic techniques are capable to detect forage internal protein structure features which are associated with forage chemical properties. Copyright © 2015 Elsevier B.V. All rights reserved.

Hyperspectral remote sensing of the responses of vegetation ecosystems to physical and biological changes of the environment

NASA Astrophysics Data System (ADS)

Krezhova, Dora; Krezhov, Kiril; Maneva, Svetla; Moskova, Irina; Petrov, Nikolay

2016-07-01

Hyperspectral remote sensing technique, based on reflectance measurements acquired in a high number of contiguous spectral bands in the visible and near infrared spectral ranges, was used to detect the influence of some environmental changes to vegetation ecosystems. Adverse physical and biological conditions give rise to morphological, physiological, and biochemical changes in the plants that affect the manner in which they interact with the light. All green vegetation species have unique spectral features, mainly because of the chlorophyll and carotenoid, and other pigments, and water content. Because spectral reflectance is a function of the illumination conditions, tissue optical properties and biochemical content of the plants it may be used to collect information on several important biophysical parameters such as color and the spectral signature of features, vegetation chlorophyll absorption characteristics, vegetation moisture content, etc. Remotely sensed data collected by means of a portable fiber-optics spectrometer in the spectral range 350-1100 nm were used to extract information on the influence of some environmental changes. Stress factors such as enhanced UV-radiation, salinity, viral infections, were applied to some young plants species (potato, tomato, plums). The test data were subjected to different digital image processing techniques. This included statistical (Student's t-criterion), first derivative and cluster analyses and some vegetation indices. Statistical analyses were carried out in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (680-720 nm) and near infrared (720-780 nm). The strong relationship, which was found between the results from the remote sensing technique and some biochemical and serological analyses (stress markers, DAS-ELISA), indicates the importance of hyperspectral reflectance data for conducting, easily and without damage, rapid assessments of plant biophysical variables. Emphasis is put on current capability and future potential of remote sensing for assessment of the plant health and on the optimum spectral regions and vegetation indices for sensing these biophysical variables.

New Infrared Emission Features and Spectral Variations in Ngc 7023

NASA Technical Reports Server (NTRS)

Werner, M. W.; Uchida, K. I.; Sellgren, K.; Marengo, M.; Gordon, K. D.; Morris, P. W.; Houck, J. R.; Stansberry, J. A.

2004-01-01

We observed the reflection nebula NGC 7023, with the Short-High module and the long-slit Short-Low and Long-Low modules of the Infrared Spectrograph on the Spitzer Space Telescope. We also present Infrared Array Camera (IRAC) and Multiband Imaging Photometer for Spitzer (MIPS) images of NGC 7023 at 3.6, 4.5, 8.0, and 24 m. We observe the aromatic emission features (AEFs) at 6.2, 7.7, 8.6, 11.3, and 12.7 m, plus a wealth of weaker features. We find new unidentified interstellar emission features at 6.7, 10.1, 15.8, 17.4, and 19.0 m. Possible identifications include aromatic hydrocarbons or nanoparticles of unknown mineralogy. We see variations in relative feature strengths, central wavelengths, and feature widths, in the AEFs and weaker emission features, depending on both distance from the star and nebular position (southeast vs. northwest).

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.

Large Area Crop Inventory Experiment (LACIE). Development of procedure M for multicrop inventory, with tests of a spring-wheat configuration

NASA Technical Reports Server (NTRS)

Horvath, R. (Principal Investigator); Cicone, R.; Crist, E.; Kauth, R. J.; Lambeck, P.; Malila, W. A.; Richardson, W.

1979-01-01

The author has identified the following significant results. An outgrowth of research and development activities in support of LACIE was a multicrop area estimation procedure, Procedure M. This procedure was a flexible, modular system that could be operated within the LACIE framework. Its distinctive features were refined preprocessing (including spatially varying correction for atmospheric haze), definition of field like spatial features for labeling, spectral stratification, and unbiased selection of samples to label and crop area estimation without conventional maximum likelihood classification.

JURASSIC Retrieval Processing

NASA Astrophysics Data System (ADS)

Blank, J.; Ungermann, J.; Guggenmoser, T.; Kaufmann, M.; Riese, M.

2012-04-01

The Gimballed Limb Observer for Radiance Imaging in the Atmosphere (GLORIA) is an aircraft based infrared limb-sounder. This presentation will give an overview of the retrieval techniques used for the analysis of data produced by the GLORIA instrument. For data processing, the JUelich RApid Spectral SImulation Code 2 (JURASSIC2) was developed. It consists of a set of programs to retrieve atmospheric profiles from GLORIA measurements. The GLORIA Michelson interferometer can run with a wide range of parameters. In the dynamics mode, spectra are generate with a medium spectral and a very high temporal and spatial resolution. Each sample can contain thousands of spectral lines for each contributing trace gas. In the JURASSIC retrieval code this is handled by using a radiative transport model based on the Emissivity Growth Approximation. Deciding which samples should be included in the retrieval is a non-trivial task and requires specific domain knowledge. To ease this problem we developed an automatic selection program by analysing the Shannon information content. By taking into account data for all relevant trace gases and instrument effects, optimal integrated spectral windows are computed. This includes considerations for cross-influence of trace gases, which has non-obvious consequence for the contribution of spectral samples. We developed methods to assess the influence of spectral windows on the retrieval. While we can not exhaustively search the whole range of possible spectral sample combinations, it is possible to optimize information content using a genetic algorithm. The GLORIA instrument is mounted with a viewing direction perpendicular to the flight direction. A gimbal frame makes it possible to move the instrument 45° to both direction. By flying on a circular path, it is possible to generate images of an area of interest from a wide range of angles. These can be analyzed in a 3D-tomographic fashion, which yields superior spatial resolution along line of site. Usually limb instruments have a resolution of several hundred kilometers. In studies we have shown to get a resolution of 35km in all horizontal directions. Even when only linear flight patterns can be realized, resolutions of ≈70km can be obtained. This technique can be used to observe features of the Upper Troposphere Lower Stratosphere (UTLS), where important mixing processes take place. Especially tropopause folds are difficult to image, as their main features need to be along line of flight when using common 1D approach.

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

Optimization of Immunolabeled Plasmonic Nanoparticles for Cell Surface Receptor Analysis

PubMed Central

Seekell, Kevin; Price, Hillel; Marinakos, Stella; Wax, Adam

2011-01-01

Noble metal nanoparticles hold great potential as optical contrast agents due to a unique feature, known as the plasmon resonance, which produces enhanced scattering and absorption at specific frequencies. The plasmon resonance also provides a spectral tunability that is not often found in organic fluorophores or other labeling methods. The ability to functionalize these nanoparticles with antibodies has led to their development as contrast agents for molecular optical imaging. In this review article, we present methods for optimizing the spectral agility of these labels. We discuss synthesis of gold nanorods, a plasmonic nanoparticle in which the plasmonic resonance can be tuned during synthesis to provide imaging within the spectral window commonly utilized in biomedical applications. We describe recent advances in our group to functionalize gold and silver nanoparticles using distinct antibodies, including EGFR, HER-2 and IGF-1, selected for their relevance to tumor imaging. Finally, we present characterization of these nanoparticle labels to verify their spectral properties and molecular specificity. PMID:21911063

The Tetracorder user guide: version 4.4

USGS Publications Warehouse

Livo, Keith Eric; Clark, Roger N.

2014-01-01

Imaging spectroscopy mapping software assists in the identification and mapping of materials based on their chemical properties as expressed in spectral measurements of a planet including the solid or liquid surface or atmosphere. Such software can be used to analyze field, aircraft, or spacecraft data; remote sensing datasets; or laboratory spectra. Tetracorder is a set of software algorithms commanded through an expert system to identify materials based on their spectra (Clark and others, 2003). Tetracorder also can be used in traditional remote sensing analyses, because some of the algorithms are a version of a matched filter. Thus, depending on the instructions fed to the Tetracorder system, results can range from simple matched filter output, to spectral feature fitting, to full identification of surface materials (within the limits of the spectral signatures of materials over the spectral range and resolution of the imaging spectroscopy data). A basic understanding of spectroscopy by the user is required for developing an optimum mapping strategy and assessing the results.

Can Measurements of the Near-Infrared Solar Spectral Irradiance be Reconciled? A New Ground-Based Assessment Between 4,000 and 10,000 cm-1

NASA Astrophysics Data System (ADS)

Elsey, Jonathan; Coleman, Marc D.; Gardiner, Tom; Shine, Keith P.

2017-10-01

The near-infrared solar spectral irradiance (SSI) is of vital importance for understanding the Earth's radiation budget, and in Earth observation applications. Differences between previously published solar spectra (including the commonly used ATLAS3 spectrum) reach up to 10% at the low wavenumber end of the 4,000-10,000 cm-1 (2.5-1 μm) spectral region. The implications for the atmospheric sciences are significant, since this spectral region contains 25% of the incoming total solar irradiance. This work details an updated analysis of the CAVIAR SSI, featuring additional analysis techniques and an updated uncertainty budget using a Monte Carlo method. We report good consistency with ATLAS3 in the 7,000-10,000 cm-1 region where there is confidence in these results due to agreement with other spectra, but 7% lower in the 4,000-7,000 cm-1 region, in general agreement with several other analyses.

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.

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

Mapping the Oman Ophiolite using TM data

NASA Technical Reports Server (NTRS)

Abrams, Michael

1987-01-01

Ophiolite terrains, considered to be the onland occurrences of oceanic crust, host a number of types of mineral deposits: volcanogenic massive sulfides, podiform chromite, and asbestos. Thematic Mapper data for the Semail Ophiolite in Oman were used to separate and map ultramafic lithologies hosting these deposits, including identification of the components of the extrusive volcanic sequence, mapping of serpentinization due to various tectonic processes, and direct identification of gossans. Thematic Mapper data were found to be extremely effective for mapping in this terrain due to the excellent spatial resolution and the presence of spectral bands which allow separation of the pertinent mineralogically caused spectral features associated with the rock types of interest.

Natural and artificial spectral edges in exoplanets

NASA Astrophysics Data System (ADS)

Lingam, Manasvi; Loeb, Abraham

2017-09-01

Technological civilizations may rely upon large-scale photovoltaic arrays to harness energy from their host star. Photovoltaic materials, such as silicon, possess distinctive spectral features, including an 'artificial edge' that is characteristically shifted in wavelength shortwards of the 'red edge' of vegetation. Future observations of reflected light from exoplanets would be able to detect both natural and artificial edges photometrically, if a significant fraction of the planet's surface is covered by vegetation or photovoltaic arrays, respectively. The stellar energy thus tapped can be utilized for terraforming activities by transferring heat and light from the day side to the night side on tidally locked exoplanets, thereby producing detectable artefacts.

An experiment to measure the energy spectrum of cosmic ray antiprotons from 100 to 1000 MeV

NASA Technical Reports Server (NTRS)

Salamon, M. H.; Price, P. B.; Barwick, S. W.; Lowder, D. M.; Ahlen, S. P.

1985-01-01

Production models were developed and the confirmation of each one had significant astrophysical impact. These include radical modifications of propagation models, cosmic ray antiprotons injection from neighboring domains of antimatter, p production by evaporating primordial black holes, and cosmic ray p's as annihilation products of supersymmetry particles that might make up the dark dynamical mass of the Galaxy. It is that p's originating from supersymmetric parents might have distinct spectral features that would survive solar modulation; in one model, higgsino annihilation proceeds through the bb quark-antiquark channel, producing a spectral bump at approx. 0.3 GeV in the p spectrum.

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

Cryogenic terahertz spectrum of (+)-methamphetamine hydrochloride and assignment using solid-state density functional theory.

PubMed

Hakey, Patrick M; Allis, Damian G; Ouellette, Wayne; Korter, Timothy M

2009-04-30

The cryogenic terahertz spectrum of (+)-methamphetamine hydrochloride from 10.0 to 100.0 cm(-1) is presented, as is the complete structural analysis and vibrational assignment of the compound using solid-state density functional theory. This cryogenic investigation reveals multiple spectral features that were not previously reported in room-temperature terahertz studies of the title compound. Modeling of the compound employed eight density functionals utilizing both solid-state and isolated-molecule methods. The results clearly indicate the necessity of solid-state simulations for the accurate assignment of solid-state THz spectra. Assignment of the observed spectral features to specific atomic motions is based on the BP density functional, which provided the best-fit solid-state simulation of the experimental spectrum. The seven experimental spectral features are the result of thirteen infrared-active vibrational modes predicted at a BP/DNP level of theory with more than 90% of the total spectral intensity associated with external crystal vibrations.

Differential coding of conspecific vocalizations in the ventral auditory cortical stream.

PubMed

Fukushima, Makoto; Saunders, Richard C; Leopold, David A; Mishkin, Mortimer; Averbeck, Bruno B

2014-03-26

The mammalian auditory cortex integrates spectral and temporal acoustic features to support the perception of complex sounds, including conspecific vocalizations. Here we investigate coding of vocal stimuli in different subfields in macaque auditory cortex. We simultaneously measured auditory evoked potentials over a large swath of primary and higher order auditory cortex along the supratemporal plane in three animals chronically using high-density microelectrocorticographic arrays. To evaluate the capacity of neural activity to discriminate individual stimuli in these high-dimensional datasets, we applied a regularized multivariate classifier to evoked potentials to conspecific vocalizations. We found a gradual decrease in the level of overall classification performance along the caudal to rostral axis. Furthermore, the performance in the caudal sectors was similar across individual stimuli, whereas the performance in the rostral sectors significantly differed for different stimuli. Moreover, the information about vocalizations in the caudal sectors was similar to the information about synthetic stimuli that contained only the spectral or temporal features of the original vocalizations. In the rostral sectors, however, the classification for vocalizations was significantly better than that for the synthetic stimuli, suggesting that conjoined spectral and temporal features were necessary to explain differential coding of vocalizations in the rostral areas. We also found that this coding in the rostral sector was carried primarily in the theta frequency band of the response. These findings illustrate a progression in neural coding of conspecific vocalizations along the ventral auditory pathway.

Differential Coding of Conspecific Vocalizations in the Ventral Auditory Cortical Stream

PubMed Central

Saunders, Richard C.; Leopold, David A.; Mishkin, Mortimer; Averbeck, Bruno B.

2014-01-01

The mammalian auditory cortex integrates spectral and temporal acoustic features to support the perception of complex sounds, including conspecific vocalizations. Here we investigate coding of vocal stimuli in different subfields in macaque auditory cortex. We simultaneously measured auditory evoked potentials over a large swath of primary and higher order auditory cortex along the supratemporal plane in three animals chronically using high-density microelectrocorticographic arrays. To evaluate the capacity of neural activity to discriminate individual stimuli in these high-dimensional datasets, we applied a regularized multivariate classifier to evoked potentials to conspecific vocalizations. We found a gradual decrease in the level of overall classification performance along the caudal to rostral axis. Furthermore, the performance in the caudal sectors was similar across individual stimuli, whereas the performance in the rostral sectors significantly differed for different stimuli. Moreover, the information about vocalizations in the caudal sectors was similar to the information about synthetic stimuli that contained only the spectral or temporal features of the original vocalizations. In the rostral sectors, however, the classification for vocalizations was significantly better than that for the synthetic stimuli, suggesting that conjoined spectral and temporal features were necessary to explain differential coding of vocalizations in the rostral areas. We also found that this coding in the rostral sector was carried primarily in the theta frequency band of the response. These findings illustrate a progression in neural coding of conspecific vocalizations along the ventral auditory pathway. PMID:24672012

A method based on IHS cylindrical transform model for quality assessment of image fusion

NASA Astrophysics Data System (ADS)

Zhu, Xiaokun; Jia, Yonghong

2005-10-01

Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.

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.

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.

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.

Spectra of Hydrogen-poor Superluminous Supernovae from the Palomar Transient Factory

NASA Astrophysics Data System (ADS)

Quimby, Robert M.; De Cia, Annalisa; Gal-Yam, Avishay; Leloudas, Giorgos; Lunnan, Ragnhild; Perley, Daniel A.; Vreeswijk, Paul M.; Yan, Lin; Bloom, Joshua S.; Cenko, S. Bradley; Cooke, Jeff; Ellis, Richard; Filippenko, Alexei V.; Kasliwal, Mansi M.; Kleiser, Io K. W.; Kulkarni, Shrinivas R.; Matheson, Thomas; Nugent, Peter E.; Pan, Yen-Chen; Silverman, Jeffrey M.; Sternberg, Assaf; Sullivan, Mark; Yaron, Ofer

2018-03-01

Most Type I superluminous supernovae (SLSNe-I) reported to date have been identified by their high peak luminosities and spectra lacking obvious signs of hydrogen. We demonstrate that these events can be distinguished from normal-luminosity SNe (including Type Ic events) solely from their spectra over a wide range of light-curve phases. We use this distinction to select 19 SLSNe-I and four possible SLSNe-I from the Palomar Transient Factory archive (including seven previously published objects). We present 127 new spectra of these objects and combine these with 39 previously published spectra, and we use these to discuss the average spectral properties of SLSNe-I at different spectral phases. We find that Mn II most probably contributes to the ultraviolet spectral features after maximum light, and we give a detailed study of the O II features that often characterize the early-time optical spectra of SLSNe-I. We discuss the velocity distribution of O II, finding that for some SLSNe-I this can be confined to a narrow range compared to relatively large systematic velocity shifts. Mg II and Fe II favor higher velocities than O II and C II, and we briefly discuss how this may constrain power-source models. We tentatively group objects by how well they match either SN 2011ke or PTF12dam and discuss the possibility that physically distinct events may have been previously grouped together under the SLSN-I label.

Spectra of Hydrogen-poor Superluminous Supernovae from the Palomar Transient Factory

DOE PAGES

Quimby, Robert M.; Cia, Annalisa De; Gal-Yam, Avishay; ...

2018-02-27

Most Type I superluminous supernovae (SLSNe-I) reported to date have been identified by their high peak luminosities and spectra lacking obvious signs of hydrogen. Here, we demonstrate that these events can be distinguished from normal-luminosity SNe (including Type Ic events) solely from their spectra over a wide range of light-curve phases. We use this distinction to select 19 SLSNe-I and four possible SLSNe-I from the Palomar Transient Factory archive (including seven previously published objects). We present 127 new spectra of these objects and combine these with 39 previously published spectra, and we use these to discuss the average spectral propertiesmore » of SLSNe-I at different spectral phases. We find that Mn ii most probably contributes to the ultraviolet spectral features after maximum light, and we give a detailed study of the O II features that often characterize the early-time optical spectra of SLSNe-I. We discuss the velocity distribution of O II, finding that for some SLSNe-I this can be confined to a narrow range compared to relatively large systematic velocity shifts. Mg II and Fe II favor higher velocities than O II and C II, and we briefly discuss how this may constrain power-source models. We tentatively group objects by how well they match either SN 2011ke or PTF12dam and discuss the possibility that physically distinct events may have been previously grouped together under the SLSN-I label.« less

Spectra of Hydrogen-poor Superluminous Supernovae from the Palomar Transient Factory

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

Quimby, Robert M.; Cia, Annalisa De; Gal-Yam, Avishay

Most Type I superluminous supernovae (SLSNe-I) reported to date have been identified by their high peak luminosities and spectra lacking obvious signs of hydrogen. Here, we demonstrate that these events can be distinguished from normal-luminosity SNe (including Type Ic events) solely from their spectra over a wide range of light-curve phases. We use this distinction to select 19 SLSNe-I and four possible SLSNe-I from the Palomar Transient Factory archive (including seven previously published objects). We present 127 new spectra of these objects and combine these with 39 previously published spectra, and we use these to discuss the average spectral propertiesmore » of SLSNe-I at different spectral phases. We find that Mn ii most probably contributes to the ultraviolet spectral features after maximum light, and we give a detailed study of the O II features that often characterize the early-time optical spectra of SLSNe-I. We discuss the velocity distribution of O II, finding that for some SLSNe-I this can be confined to a narrow range compared to relatively large systematic velocity shifts. Mg II and Fe II favor higher velocities than O II and C II, and we briefly discuss how this may constrain power-source models. We tentatively group objects by how well they match either SN 2011ke or PTF12dam and discuss the possibility that physically distinct events may have been previously grouped together under the SLSN-I label.« less

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.

Fusion of shallow and deep features for classification of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

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.

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.

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.

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?

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.

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed ADF features can effectively improve the accuracy of urban scene classification, with a significant increase in overall accuracy (3.8-11.7%) compared to using the spectral bands alone. Furthermore, the results indicated the superiority of the proposed ADFs in distinguishing between the spectrally similar and complex man-made classes, including roads and various types of buildings (e.g., high buildings, urban villages, and residential apartments).

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.

Spectral Observations and Analyses of Low-Redshift Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Silverman, Jeffrey Michael

The explosive deaths of stars, known as a supernovae (SNe), have been critical to our understanding of the Universe for centuries. An introduction to SNe, their importance in astronomy, and how we observe them is given in Chapter 1. In the second Chapter, I present the full BSNIP sample which consists of 1298 low-redshift (z ≤ 0.2) optical spectra of 582 SNe Ia observed from 1989 through the end of 2008. I describe our spectral classification scheme (using the SuperNova IDentification code, SNID; Blondin & Tonry 2007), utilizing my newly constructed set of SNID spectral templates. These templates allow me to accurately spectroscopically classify the entire BSNIP dataset, and by doing so I am able to reclassify a handful of objects as bona fide SNe Ia and a few other objects as members of some of the peculiar SN Ia subtypes. In fact, the BSNIP dataset includes spectra of nearly 90 spectroscopically peculiar SNe Ia. I also present spectroscopic host-galaxy redshifts of some SNe Ia where these values were previously unknown. I present measurements of spectral features of 432 low-redshift ( z < 0.1) optical spectra within 20 d of maximum brightness of 261 SNe Ia from the BSNIP sample in the third Chapter. I describe in detail my method of automated, robust spectral feature definition and measurement which expands upon similar previous studies. Using this procedure, I attempt to measure expansion velocities, (pseudo-)equivalent widths (pEWs), spectral feature depths, and fluxes at the center and endpoints of each of nine major spectral feature complexes. A sanity check of the consistency of the measurements is performed using the BSNIP data (as well as a separate spectral dataset). I investigate how velocity and pEW evolve with time and how they correlate with each other. Various spectral classification schemes are employed and quantitative spectral differences among the subclasses are investigated. Several ratios of pEW values are calculated and studied. Furthermore, SNe Ia that show strong evidence for interaction with circumstellar material or an aspherical explosion are found to have the largest near-maximum expansion velocities and pEWs, possibly linking extreme values of spectral observables with specific progenitor or explosion scenarios. The fourth Chapter of this Thesis presents comparisons of spectral feature measurements to photometric properties of 115 low-redshift (z < 0.1) SNe Ia with optical spectra within 5 d of maximum brightness. The spectral data come from the BSNIP sample described in Chapter 2, and the photometric data come mainly from the Lick Observatory Supernova Search (LOSS) and are published by Ganeshalingam et al. (2010). The spectral measurements come from BSNIP II (Chapter 3 of this Thesis) and the light-curve fits and photometric parameters can be found in Ganeshalingam et al. (in preparation). A variety of previously proposed correlations between spectral and photometric parameters are investigated using the large and self-consistent BSNIP dataset. We also use a combination of light-curve parameters (specifically the SALT2 stretch and color parameters x1 and c) and spectral measurements to calculate distance moduli. The residuals from these models is then compared to the standard model which only uses light-curve stretch and color. The pEW of Si II lambda4000 is found to be a good indicator of light-curve width and the pEWs of the Mg II and Fe II complexes are relatively good proxies for color. Chapter 5 presents and analyzes optical photometry and spectra of the extremely luminous and slowly evolving Type Ia SN 2009dc, and offers evidence that it is a super-Chandrasekhar mass (SC) SN Ia and thus had a SC white dwarf (WD) progenitor. I calculate a lower limit to the peak bolometric luminosity of ˜2.4x1043 erg s-1, though the actual value is likely almost 40% larger. The high luminosity and low expansion velocities of SN 2009dc lead to a derived WD progenitor mass of more than 2 MSun and a 56Ni mass of about 1.4--1.7 MSun. I propose that the host galaxy of SN 2009dc underwent a gravitational interaction with a neighboring galaxy in the relatively recent past. This may have led to a sudden burst of star formation which could have produced the SC WD progenitor of SN 2009dc and likely turned the neighboring galaxy into a "post-starburst galaxy." (Abstract shortened by UMI.)

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

Quantitative Hyperspectral Reflectance Imaging

PubMed Central

Klein, Marvin E.; Aalderink, Bernard J.; Padoan, Roberto; de Bruin, Gerrit; Steemers, Ted A.G.

2008-01-01

Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms. PMID:27873831

Low Temperature Reflectance Spectra of Titan Tholins

NASA Technical Reports Server (NTRS)

Roush, T. L.; Dalton, J. B.; Fonda, Mark (Technical Monitor)

2001-01-01

Compositional interpretation of remotely obtained reflectance spectra of outer solar system surfaces is achieved by a variety of methods. These include matching spectral curves, matching spectral features, quantitative spectral interpretation, and theoretical modeling of spectra. All of these approaches rely upon laboratory measurements of one kind or another. The bulk of these laboratory measurements are obtained with the sample of interest at ambient temperatures and pressures. However, surface temperatures of planets, satellites, and asteroids in the outer solar system are significantly cooler than ambient laboratory conditions on Earth. The infrared spectra of many materials change as a function of temperature. As has been recently demonstrated it is important to assess what effects colder temperatures have on spectral properties and hence, compositional interpretations. Titan tholin is a solid residue created by energetic processing of H-, C-, and N-bearing gases. Such residues can also be created by energetic processing if the gases are condensed into ices. Titan tholin has been suggested as a coloring agent for several surfaces in the outer solar system. Here we report laboratory measurements of Titan tholin at a temperature of 100 K and compare these to measurements of the same sample near room temperature. At low temperature the absorption features beyond 1 micrometer narrow slightly. At wavelengths greater than approx. 0.8 micrometer the overall reflectance of the sample decreases slightly making the sample less red at low temperatures. We will discuss the implications of the laboratory measurements for interpretation of cold outer solar system surfaces.

Visible Near-infrared Spectral Evolution of Irradiated Mixed Ices and Application to Kuiper Belt Objects and Jupiter Trojans

NASA Astrophysics Data System (ADS)

Poston, Michael J.; Mahjoub, Ahmed; Ehlmann, Bethany L.; Blacksberg, Jordana; Brown, Michael E.; Carlson, Robert W.; Eiler, John M.; Hand, Kevin P.; Hodyss, Robert; Wong, Ian

2018-04-01

Understanding the history of Kuiper Belt Objects and Jupiter Trojans will help to constrain models of solar system formation and dynamical evolution. Laboratory simulations of a possible thermal and irradiation history of these bodies were conducted on ice mixtures while monitoring their spectral properties. These simulations tested the hypothesis that the presence or absence of sulfur explains the two distinct visible near-infrared spectral groups observed in each population and that Trojans and KBOs share a common formation location. Mixed ices consisting of water, methanol, and ammonia, in mixtures both with and without hydrogen sulfide, were deposited and irradiated with 10 keV electrons. Deposition and initial irradiation were performed at 50 K to simulate formation at 20 au in the early solar system, then heated to Trojan-like temperatures and irradiated further. Finally, irradiation was concluded and resulting samples were observed during heating to room temperature. Results indicated that the presence of sulfur resulted in steeper spectral slopes. Heating through the 140–200 K range decreased the slopes and total reflectance for both mixtures. In addition, absorption features at 410, 620, and 900 nm appeared under irradiation, but only in the H2S-containing mixture. These features were lost with heating once irradiation was concluded. While the results reported here are consistent with the hypothesis, additional work is needed to address uncertainties and to simulate conditions not included in the present work.

Combined VIS-IR spectrometer with vertical probe beam

NASA Astrophysics Data System (ADS)

Protopopov, V.

2017-12-01

A prototype of a combined visible-infrared spectrometer with a vertical probe beam is designed and tested. The combined spectral range is 0.4-20 μ with spatial resolution 1 mm. Basic features include the ability to measure both visibly transparent and opaque substances, as well as buried structures, such as in semiconductor industry; horizontal orientation of a sample, including semiconductor wafers; and reflection mode of operation, delivering twice the sensitivity compared to the transmission mode.

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

Meeting the Cool Neighbors. XII. An Optically Anchored Analysis of the Near-infrared Spectra of L Dwarfs

NASA Astrophysics Data System (ADS)

Cruz, Kelle L.; Núñez, Alejandro; Burgasser, Adam J.; Abrahams, Ellianna; Rice, Emily L.; Reid, I. Neill; Looper, Dagny

2018-01-01

Discrepancies between competing optical and near-infrared (NIR) spectral typing systems for L dwarfs have motivated us to search for a classification scheme that ties the optical and NIR schemes together, and addresses complexities in the spectral morphology. We use new and extant optical and NIR spectra to compile a sample of 171 L dwarfs, including 27 low-gravity β and γ objects, with spectral coverage from 0.6–2.4 μm. We present 155 new low-resolution NIR spectra and 19 new optical spectra. We utilize a method for analyzing NIR spectra that partially removes the broad-band spectral slope and reveals similarities in the absorption features between objects of the same optical spectral type. Using the optical spectra as an anchor, we generate near-infrared spectral average templates for L0–L8, L0–L4γ, and L0–L1β type dwarfs. These templates reveal that NIR spectral morphologies are correlated with the optical types. They also show the range of spectral morphologies spanned by each spectral type. We compare low-gravity and field-gravity templates to provide recommendations on the minimum required observations for credibly classifying low-gravity spectra using low-resolution NIR data. We use the templates to evaluate the existing NIR spectral standards and propose new ones where appropriate. Finally, we build on the work of Kirkpatrick et al. to provide a spectral typing method that is tied to the optical and can be used when only H or K band data are available. The methods we present here provide resolutions to several long-standing issues with classifying L dwarf spectra and could also be the foundation for a spectral classification scheme for cloudy exoplanets.

Connecting infrared spectra with plant traits to identify species

NASA Astrophysics Data System (ADS)

Buitrago, Maria F.; Skidmore, Andrew K.; Groen, Thomas A.; Hecker, Christoph A.

2018-05-01

Plant traits are used to define species, but also to evaluate the health status of forests, plantations and crops. Conventional methods of measuring plant traits (e.g. wet chemistry), although accurate, are inefficient and costly when applied over large areas or with intensive sampling. Spectroscopic methods, as used in the food industry and mineralogy, are nowadays applied to identify plant traits, however, most studies analysed visible to near infrared, while infrared spectra of longer wavelengths have been little used for identifying the spectral differences between plant species. This study measured the infrared spectra (1.4-16.0 μm) on individual, fresh leaves of 19 species (from herbaceous to woody species), as well as 14 leaf traits for each leaf. The results describe at which wavelengths in the infrared the leaves' spectra can differentiate most effectively between these plant species. A Quadratic Discrimination Analysis (QDA) shows that using five bands in the SWIR or the LWIR is enough to accurately differentiate these species (Kappa: 0.93, 0.94 respectively), while the MWIR has a lower classification accuracy (Kappa: 0.84). This study also shows that in the infrared spectra of fresh leaves, the identified species-specific features are correlated with leaf traits as well as changes in their values. Spectral features in the SWIR (1.66, 1.89 and 2.00 μm) are common to all species and match the main features of pure cellulose and lignin spectra. The depth of these features varies with changes of cellulose and leaf water content and can be used to differentiate species in this region. In the MWIR and LWIR, the absorption spectra of leaves are formed by key species-specific traits including lignin, cellulose, water, nitrogen and leaf thickness. The connection found in this study between leaf traits, features and spectral signatures are novel tools to assist when identifying plant species by spectroscopy and remote sensing.

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

PubMed Central

Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Hajnal, Joseph V.; Duncan, John S.; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2012-01-01

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study. PMID:22523539

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

Neutron spectrometry for UF 6 enrichment verification in storage cylinders

DOE PAGES

Mengesha, Wondwosen; Kiff, Scott D.

2015-01-29

Verification of declared UF 6 enrichment and mass in storage cylinders is of great interest in nuclear material nonproliferation. Nondestructive assay (NDA) techniques are commonly used for safeguards inspections to ensure accountancy of declared nuclear materials. Common NDA techniques used include gamma-ray spectrometry and both passive and active neutron measurements. In the present study, neutron spectrometry was investigated for verification of UF 6 enrichment in 30B storage cylinders based on an unattended and passive measurement approach. MCNP5 and Geant4 simulated neutron spectra, for selected UF 6 enrichments and filling profiles, were used in the investigation. The simulated neutron spectra weremore » analyzed using principal component analysis (PCA). The PCA technique is a well-established technique and has a wide area of application including feature analysis, outlier detection, and gamma-ray spectral analysis. Results obtained demonstrate that neutron spectrometry supported by spectral feature analysis has potential for assaying UF 6 enrichment in storage cylinders. Thus the results from the present study also showed that difficulties associated with the UF 6 filling profile and observed in other unattended passive neutron measurements can possibly be overcome using the approach presented.« less

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. ...

THE ORION FINGERS: NEAR-IR SPECTRAL IMAGING OF AN EXPLOSIVE OUTFLOW

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

Youngblood, Allison; Bally, John; Ginsburg, Adam, E-mail: allison.youngblood@colorado.edu

2016-06-01

We present near-IR (1.1–2.4 μ m) position–position–velocity cubes of the 500 year old Orion BN/KL explosive outflow with spatial resolution 1″ and spectral resolution 86 km s{sup −1}. We construct integrated intensity maps free of continuum sources of 15 H{sub 2} and [Fe ii] lines while preserving kinematic information of individual outflow features. Included in the detected H{sub 2} lines are the 1-0 S(1) and 1-0 Q(3) transitions, allowing extinction measurements across the outflow. Additionally, we present dereddened flux ratios for over two dozen outflow features to allow for the characterization of the true excitation conditions of the BN/KL outflow. All of themore » ratios show the dominance of the shock excitation of the H{sub 2} emission, although some features exhibit signs of fluorescent excitation from stellar radiation or J-type shocks. We also detect tracers of the PDR/ionization front north of the Trapezium stars in [O i] and [Fe ii] and analyze other observed outflows not associated with the BN/KL outflow.« less

Multi-Modal Ultra-Widefield Imaging Features in Waardenburg Syndrome

PubMed Central

Choudhry, Netan; Rao, Rajesh C.

2015-01-01

Background Waardenburg syndrome is characterized by a group of features including; telecanthus, a broad nasal root, synophrys of the eyebrows, piedbaldism, heterochromia irides, and deaf-mutism. Hypopigmentation of the choroid is a unique feature of this condition examined with multi-modal Ultra-Widefield Imaging in this report. Material/Methods Report of a single case. Results Bilateral symmetric choroidal hypopigmentation was observed with hypoautofluorescence in the region of hypopigmentation. Fluorescein angiography revealed a normal vasculature, however a thickened choroid was seen on Enhanced-Depth Imaging Spectral-Domain OCT (EDI SD-OCT). Conclusion(s) Choroidal hypopigmentation is a unique feature of Waardenburg syndrome, which can be visualized with ultra-widefield fundus autofluorescence. The choroid may also be thickened in this condition and its thickness measured with EDI SD-OCT. PMID:26114849

Remote Sensing in Archaeology: Visible Temporal Change of Archaeological Features of the Peten, Guatemala

NASA Technical Reports Server (NTRS)

Lowry, James D., Jr.

1999-01-01

The purpose of this archaeological research was two-fold; the location of Mayan sites and features in order to learn more of this cultural group, and the (cultural) preservation of these sites and features for the future using Landsat Thematic Mapper (TM) images. Because the rainy season, traditionally at least, lasts about six months (about June to December), the time of year the image is acquired plays an important role in spectral reflectance. Images from 1986, 1995, and 1997 were selected because it was felt they would provide the best opportunity for success in layering different bands from different years together to attempt to see features not completely visible in any one year. False-color composites were created including bands 3, 4, and 5 using a mixture of years and bands. One particular combination that yielded tremendously interesting results included band 5 from 1997, band 4 from 1995, and band 3 from 1986. A number of straight linear features (probably Mayan causeways) run through the bajos that Dr. Sever believes are features previously undiscovered. At this point, early indications are that this will be a successful method for locating "new" Mayan archaeological features in the Peten.

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).

Assessment of Homomorphic Analysis for Human Activity Recognition from Acceleration Signals.

PubMed

Vanrell, Sebastian Rodrigo; Milone, Diego Humberto; Rufiner, Hugo Leonardo

2017-07-03

Unobtrusive activity monitoring can provide valuable information for medical and sports applications. In recent years, human activity recognition has moved to wearable sensors to deal with unconstrained scenarios. Accelerometers are the preferred sensors due to their simplicity and availability. Previous studies have examined several \\azul{classic} techniques for extracting features from acceleration signals, including time-domain, time-frequency, frequency-domain, and other heuristic features. Spectral and temporal features are the preferred ones and they are generally computed from acceleration components, leaving the acceleration magnitude potential unexplored. In this study, based on homomorphic analysis, a new type of feature extraction stage is proposed in order to exploit discriminative activity information present in acceleration signals. Homomorphic analysis can isolate the information about whole body dynamics and translate it into a compact representation, called cepstral coefficients. Experiments have explored several configurations of the proposed features, including size of representation, signals to be used, and fusion with other features. Cepstral features computed from acceleration magnitude obtained one of the highest recognition rates. In addition, a beneficial contribution was found when time-domain and moving pace information was included in the feature vector. Overall, the proposed system achieved a recognition rate of 91.21% on the publicly available SCUT-NAA dataset. To the best of our knowledge, this is the highest recognition rate on this dataset.

Spectral features of LO phonon sidebands in luminescence of free excitons in GaN

NASA Astrophysics Data System (ADS)

Xu, S. J.; Li, G. Q.; Xiong, S.-J.; Tong, S. Y.; Che, C. M.; Liu, W.; Li, M. F.

2005-06-01

In the paper a combined experimental and theoretical investigation of the longitudinal optical phonon sidebands (PSBs) in the luminescence of free excitons in GaN at moderately high temperatures was reported. The spectral features, including line broadening, shift, and asymmetry of the one- and two-phonon PSBs, were revealed both experimentally and theoretically. It is found that the linewidth of the one-phonon PSB is surprisingly always larger than that of the two-phonon PSB in the interested temperature range. Moreover, the thermal broadening rates of the one- and two-phonon PSBs are considerably different. We adopted the Segall-Mahan theory [B. Segall and G. D. Mahan, Phys. Rev. 171, 935 (1968)] to compute the PSB spectra of the free excitons in GaN. Only one adjustable parameter, the effective mass of the holes, was used in the calculations. For the one-phonon PSB, an excellent agreement between theory and experiment is achieved when an adequate effective mass of the holes was used.

System-independent characterization of materials using dual-energy computed tomography

DOE PAGES

Azevedo, Stephen G.; Martz, Jr., Harry E.; Aufderheide, III, Maurice B.; ...

2016-02-01

In this study, we present a new decomposition approach for dual-energy computed tomography (DECT) called SIRZ that provides precise and accurate material description, independent of the scanner, over diagnostic energy ranges (30 to 200 keV). System independence is achieved by explicitly including a scanner-specific spectral description in the decomposition method, and a new X-ray-relevant feature space. The feature space consists of electron density, ρ e, and a new effective atomic number, Z e, which is based on published X-ray cross sections. Reference materials are used in conjunction with the system spectral response so that additional beam-hardening correction is not necessary.more » The technique is tested against other methods on DECT data of known specimens scanned by diverse spectra and systems. Uncertainties in accuracy and precision are less than 3% and 2% respectively for the (ρ e, Z e) results compared to prior methods that are inaccurate and imprecise (over 9%).« less

Comparison of visible and near-infrared reflectance spectra of CM2 carbonaceous chondrites and primitive asteroids

NASA Technical Reports Server (NTRS)

Vilas, F.; Hiroi, T.; Zolensky, M. E.

1993-01-01

Spectra of primitive asteroids (defined as C, P, and D classes and associated subclasses) were compared to the limited number of spectra of CM2 carbonaceous chondrites. An absorption feature located at 0.7 microns attributed to an Fe(+2) - Fe(+3) charge transfer absorption in iron oxides in phyllosilicates is apparent in some of the CM2 carbonaceous chondrite spectra and many of the asteroid spectra. Sawyer found a correlation between the area of the 0.7 micron feature and the mean semimajor axis of the asteroids. Spectra of a larger sample of carbonaceous chondrites, including 7 CM2 chondrites, covering a spectral interval of 0.30-2.5 microns were recently obtained using the Relab instrument at Brown University. These spectra were compared with spectrophotometric asteroid observations in a separate abstract. Those spectra of CM2 chondrites were isolated into the UV, visible and near-infrared spectral regions in order to compare them with high-quality narrowband reflectance spectra.

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.

Relationship between channel interaction and spectral-ripple discrimination in cochlear implant usersa

PubMed Central

Jones, Gary L.; Ho Won, Jong; Drennan, Ward R.; Rubinstein, Jay T.

2013-01-01

Cochlear implant (CI) users can achieve remarkable speech understanding, but there is great variability in outcomes that is only partially accounted for by age, residual hearing, and duration of deafness. Results might be improved with the use of psychophysical tests to predict which sound processing strategies offer the best potential outcomes. In particular, the spectral-ripple discrimination test offers a time-efficient, nonlinguistic measure that is correlated with perception of both speech and music by CI users. Features that make this “one-point” test time-efficient, and thus potentially clinically useful, are also connected to controversy within the CI field about what the test measures. The current work examined the relationship between thresholds in the one-point spectral-ripple test, in which stimuli are presented acoustically, and interaction indices measured under the controlled conditions afforded by direct stimulation with a research processor. Results of these studies include the following: (1) within individual subjects there were large variations in the interaction index along the electrode array, (2) interaction indices generally decreased with increasing electrode separation, and (3) spectral-ripple discrimination improved with decreasing mean interaction index at electrode separations of one, three, and five electrodes. These results indicate that spectral-ripple discrimination thresholds can provide a useful metric of the spectral resolution of CI users. PMID:23297914

Relationship between channel interaction and spectral-ripple discrimination in cochlear implant users.

PubMed

Jones, Gary L; Won, Jong Ho; Drennan, Ward R; Rubinstein, Jay T

2013-01-01

Cochlear implant (CI) users can achieve remarkable speech understanding, but there is great variability in outcomes that is only partially accounted for by age, residual hearing, and duration of deafness. Results might be improved with the use of psychophysical tests to predict which sound processing strategies offer the best potential outcomes. In particular, the spectral-ripple discrimination test offers a time-efficient, nonlinguistic measure that is correlated with perception of both speech and music by CI users. Features that make this "one-point" test time-efficient, and thus potentially clinically useful, are also connected to controversy within the CI field about what the test measures. The current work examined the relationship between thresholds in the one-point spectral-ripple test, in which stimuli are presented acoustically, and interaction indices measured under the controlled conditions afforded by direct stimulation with a research processor. Results of these studies include the following: (1) within individual subjects there were large variations in the interaction index along the electrode array, (2) interaction indices generally decreased with increasing electrode separation, and (3) spectral-ripple discrimination improved with decreasing mean interaction index at electrode separations of one, three, and five electrodes. These results indicate that spectral-ripple discrimination thresholds can provide a useful metric of the spectral resolution of CI users.

Ion Spectral Structures Observed by the Van Allen Probes and Cluster

NASA Astrophysics Data System (ADS)

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

2014-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. Previous studies have revealed single "nose-like" structures occurring alone and simultaneous nose-like structures (up to three). In this study we also include signatures of new types of ion structure, namely "trunk-like" and "tusk-like" structures. All the ion structures are named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. They constitute the observational signatures of ion acceleration, transport, and loss in the global magnetosphere. Multi-spacecraft analysis of these structures is important to understand their spatial distribution and temporal evolution. Mass spectrometers onboard Cluster (in a polar orbit) and the Van Allen Probes (in an equatorial orbit) measure energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet, where these ion structures are observed. We present a statistical study of the ion structures, using >1-year measurements from the two missions during the Van Allen Probes era. The results provide important details about the spatial distribution (dependence on geocentric distance and magnetic local time), spectral features of the structures (e.g., characteristic energy and differences among species), and geomagnetic and solar wind conditions under which these structures occur.

Laboratory IR Studies and Astrophysical Implications of C2H2-Containing Binary Ices

NASA Technical Reports Server (NTRS)

Knez, C.; Moore, M.; Ferrante, R.; Hudson, R.

2012-01-01

Studies of molecular hot cores and protostellar environments have shown that the observed abundance of gas-phase acetylene (C2H2) cannot be matched by chemical models without the inclusion of C2H2 molecules subliming from icy grain mantles. Searches for infrared (IR) spectral features of solid-phase acetylene are under way, but few laboratory reference spectra of C2H2 in icy mixtures, which are needed for spectral fits to observational data, have been published. Here, we report a systematic study of the IR spectra of condensed-phase pure acetylene and acetylene in ices dominated by carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), and water (H2O). We present new spectral data for these ices, including band positions and intrinsic band strengths. For each ice mixture and concentration, we also explore the dependence of acetylene's nu5-band position (743 cm-1, 13.46 micrometers) and FWHM on temperature. Our results show that the nu5 feature is much more cleanly resolved in ices dominated by non-polar and low-polarity molecules, specifically CO, CO2, and CH4, than in mixtures dominated by H2O-ice. We compare our laboratory ice spectra with observations of a quiescent region in Serpens.

Searching for Aqueous Activity on Mars through Analyses of OMEGA Spectra

NASA Astrophysics Data System (ADS)

Bishop, J. L.; Bibring, J.-P.; Dyar, M. D.; Gendrin, A.; Lane, M. D.; Mustard, J. F.; Parente, M.; Poulet, F.

2005-08-01

Analyses of OMEGA spectra have shown the presence of sulfate and clay minerals in a number of regions including Valles Marineris, Nili Fossae and Terra Meridiani (1-4). We are searching for spectral features associated with these minerals in OMEGA image cubes and are using expanded spectral libraries to further characterize these features. Shown below are three OMEGA spectra from the Valles Marineris and Syrtis Major regions, identified from top to bottom as containing kieserite, nontronite, and polyhydrated sulfates (2,3). They are compared in the figure with spectra of nontronite and of the hydrous sulfate minerals szomolnokite (Fe2+SO4H2O kieserite group) and rozenite (Fe2+S44H2O starkeyite group). We seek to identify and characterize areas on Mars where it is possible to refine the mineralogical interpretations. We are searching for locations where minerals such as szomolnokite or rozenite may be the spectrally dominant component in spectra characterized so far as monohydrated and polyhydrated sulfates. 1) J.-P. Bibring et al., Science 307, 1576 (2005). 2) A. Gendrin et al., 2nd Conf. on Early Mars, Jackson Hole, Wyoming 2004. 3) A. Gendrin et al., Science 307, 1587 (2005). 4) J. F. Mustard et al., LPSC #1341 (2005).

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.

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.

Characterizing mammographic images by using generic texture features

PubMed Central

2012-01-01

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

On-target diagnosing of few-cycle pulses by high-order-harmonic generation

NASA Astrophysics Data System (ADS)

Brambila, Danilo S.; Husakou, Anton; Ivanov, Misha; Zhavoronkov, Nickolai

2017-12-01

We propose an approach to determine the residual phase distortion directly in the interaction region of few-cycle laser radiation with a gaseous target. We describe how the spectra of the generated high harmonics measured as a function of externally introduced dispersion into the driving few-cycle laser pulse can be used to decode small amounts of second- and third-order spectral phase, including the sign. The diagnosis is based on the analysis of several key features in the high-harmonic spectrum: the depth of spectral modulation, the position of the cutoff, and the symmetry of the spectrum with respect to the introduced dispersion. The approach is applicable to pulses without carrier-envelope phase (CEP) stabilization. Surprisingly, we find that for nearly-single-cycle pulses with nonstabilized CEP, deep spectral modulations in the harmonic spectra emerge for positively rather than negatively chirped pulses, in contrast to the case of CEP-stabilized pulses.

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.

Water in the Early Solar System: Infrared Studies of Aqueously Altered and Minimally Processed Asteroids

NASA Astrophysics Data System (ADS)

McAdam, Margaret M.

This thesis investigates connections between low albedo asteroids and carbonaceous chondrite meteorites using spectroscopy. Meteorites and asteroids preserve information about the early solar system including accretion processes and parent body processes active on asteroids at these early times. One process of interest is aqueous alteration. This is the chemical reaction between coaccreted water and silicates producing hydrated minerals. Some carbonaceous chondrites have experienced extensive interactions with water through this process. Since these meteorites and their parent bodies formed close to the beginning of the Solar System, these asteroids and meteorites may provide clues to the distribution, abundance and timing of water in the Solar nebula at these times. Chapter 2 of this thesis investigates the relationships between extensively aqueously altered meteorites and their visible, near and mid-infrared spectral features in a coordinated spectral-mineralogical study. Aqueous alteration is a parent body process where initially accreted anhydrous minerals are converted into hydrated minerals in the presence of coaccreted water. Using samples of meteorites with known bulk properties, it is possible to directly connect changes in mineralogy caused by aqueous alteration with spectral features. Spectral features in the mid-infrared are found to change continuously with increasing amount of hydrated minerals or degree of alteration. Building on this result, the degrees of alteration of asteroids are estimated in a survey of new asteroid data obtained from SOFIA and IRTF as well as archived the Spitzer Space Telescope data. 75 observations of 73 asteroids are analyzed and presented in Chapter 4. Asteroids with hydrated minerals are found throughout the main belt indicating that significant ice must have been present in the disk at the time of carbonaceous asteroid accretion. Finally, some carbonaceous chondrite meteorites preserve amorphous iron-bearing materials that formed through disequilibrium condensation in the disk. These materials are readily destroyed in parent body processes so their presence indicates the meteorite/asteroid has undergone minimal parent body processes since the time of accretion. Presented in Chapter 3 is the spectral signature of meteorites that preserve significant amorphous iron-bearing materials and the identification of an asteroid, (93) Minerva, that also appears to preserve these materials.

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

Prediction of spectral acceleration response ordinates based on PGA attenuation

USGS Publications Warehouse

Graizer, V.; Kalkan, E.

2009-01-01

Developed herein is a new peak ground acceleration (PGA)-based predictive model for 5% damped pseudospectral acceleration (SA) ordinates of free-field horizontal component of ground motion from shallow-crustal earthquakes. The predictive model of ground motion spectral shape (i.e., normalized spectrum) is generated as a continuous function of few parameters. The proposed model eliminates the classical exhausted matrix of estimator coefficients, and provides significant ease in its implementation. It is structured on the Next Generation Attenuation (NGA) database with a number of additions from recent Californian events including 2003 San Simeon and 2004 Parkfield earthquakes. A unique feature of the model is its new functional form explicitly integrating PGA as a scaling factor. The spectral shape model is parameterized within an approximation function using moment magnitude, closest distance to the fault (fault distance) and VS30 (average shear-wave velocity in the upper 30 m) as independent variables. Mean values of its estimator coefficients were computed by fitting an approximation function to spectral shape of each record using robust nonlinear optimization. Proposed spectral shape model is independent of the PGA attenuation, allowing utilization of various PGA attenuation relations to estimate the response spectrum of earthquake recordings.

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.

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.

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.

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.

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.

Spectral quality requirements for effluent identification

NASA Astrophysics Data System (ADS)

Czerwinski, R. N.; Seeley, J. A.; Wack, E. C.

2005-11-01

We consider the problem of remotely identifying gaseous materials using passive sensing of long-wave infrared (LWIR) spectral features at hyperspectral resolution. Gaseous materials are distinguishable in the LWIR because of their unique spectral fingerprints. A sensor degraded in capability by noise or limited spectral resolution, however, may be unable to positively identify contaminants, especially if they are present in low concentrations or if the spectral library used for comparisons includes materials with similar spectral signatures. This paper will quantify the relative importance of these parameters and express the relationships between them in a functional form which can be used as a rule of thumb in sensor design or in assessing sensor capability for a specific task. This paper describes the simulation of remote sensing datacontaining a gas cloud.In each simulation, the spectra are degraded in spectral resolution and through the addition of noise to simulate spectra collected by sensors of varying design and capability. We form a trade space by systematically varying the number of sensor spectral channels and signal-to-noise ratio over a range of values. For each scenario, we evaluate the capability of the sensor for gas identification by computing the ratio of the F-statistic for the truth gas tothe same statistic computed over the rest of the library.The effect of the scope of the library is investigated as well, by computing statistics on the variability of the identification capability as the library composition is varied randomly.

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.

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

SIGN SINGULARITY AND FLARES IN SOLAR ACTIVE REGION NOAA 11158

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

Sorriso-Valvo, L.; De Vita, G.; Kazachenko, M. D.

Solar Active Region NOAA 11158 has hosted a number of strong flares, including one X2.2 event. The complexity of current density and current helicity are studied through cancellation analysis of their sign-singular measure, which features power-law scaling. Spectral analysis is also performed, revealing the presence of two separate scaling ranges with different spectral index. The time evolution of parameters is discussed. Sudden changes of the cancellation exponents at the time of large flares and the presence of correlation with Extreme-Ultra-Violet and X-ray flux suggest that eruption of large flares can be linked to the small-scale properties of the current structures.

Spectral-element simulation of two-dimensional elastic wave propagation in fully heterogeneous media on a GPU cluster

NASA Astrophysics Data System (ADS)

Rudianto, Indra; Sudarmaji

2018-04-01

We present an implementation of the spectral-element method for simulation of two-dimensional elastic wave propagation in fully heterogeneous media. We have incorporated most of realistic geological features in the model, including surface topography, curved layer interfaces, and 2-D wave-speed heterogeneity. To accommodate such complexity, we use an unstructured quadrilateral meshing technique. Simulation was performed on a GPU cluster, which consists of 24 core processors Intel Xeon CPU and 4 NVIDIA Quadro graphics cards using CUDA and MPI implementation. We speed up the computation by a factor of about 5 compared to MPI only, and by a factor of about 40 compared to Serial implementation.

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.

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.

Reflectance and Mossbauer spectroscopy of ferrihydrite-montmorillonite assemblages as Mars soil analog materials

NASA Technical Reports Server (NTRS)

Bishop, J. L.; Pieters, C. M.; Burns, R. G.; Chang, S. (Principal Investigator)

1993-01-01

Spectroscopic analyses show that Fe(3+)-doped smectites prepared in the laboratory exhibit important similarities to the soils on Mars. Ferrihydrite has been identified as the interlayer ferric component in Fe(3+)-doped smectites by a low quadrupole splitting and magnetic field strength of approximately 48 tesla in Mossbauer spectra measured at 4.2 K, as well as a crystal field transition at 0.92 micrometer. Ferrihydrite in these smectites explains features in the visible-near infrared region that resemble the energies and band strengths of features in reflectance spectra observed for several bright regions on Mars. Clay silicates have met resistance in the past as Mars soil analogs because terrestrial clay silicates exhibit prominent hydrous spectral features at 1.4, 1.9, and 2.2 micrometers; and these are observed weakly, if at all, in reflectance spectra of Mars. However, several mechanisms can weaken or compress these features, including desiccation under low-humidity conditions. The hydration properties of the interlayer cations also effect band strengths, such that a ferrihydrite-bearing smectite in the Martian environment would exhibit a 1.9 micrometers H2O absorption that is even weaker than the 2.2 micrometers structural OH absorption. Mixing experiments demonstrate that infrared spectral features of clays can be significantly suppressed and that the reflectance can be significantly darkened by mixing with only a few percent of a strongly absorbing opaque material. Therefore, the absolute reflectance of a soil on Mars may be disproportionately sensitive to a minor component. For this reason, the shape and position of spectral features and the chemical composition of potential analogs are of utmost importance in assessing the composition of the soil on Mars. Given the remarkable similarity between visible-infrared reflectance spectra of soils in bright regions on Mars and Fe(3+)-doped montmorillonites, coupled with recent observations of smectites in SNC meteorites and a weak 2.2 micrometers absorption in some Mars soils, ferrihydrite-bearing smectites warrant serious consideration as a Mars soil analog.

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.

Relationship of carbohydrate molecular spectroscopic features in combined feeds to carbohydrate utilization and availability in ruminants

NASA Astrophysics Data System (ADS)

Zhang, Xuewei; Yu, Peiqiang

To date, there is no study on the relationship between carbohydrate (CHO) molecular structures and nutrient availability of combined feeds in ruminants. The objective of this study was to use molecular spectroscopy to reveal the relationship between CHO molecular spectral profiles (in terms of functional groups (biomolecular, biopolymer) spectral peak area and height intensity) and CHO chemical profiles, CHO subfractions, energy values, and CHO rumen degradation kinetics of combined feeds of hulless barley with pure wheat dried distillers grains with solubles (DDGS) at five different combination ratios (hulless barley to pure wheat DDGS: 100:0, 75:25, 50:50, 25:75, 0:100). The molecular spectroscopic parameters assessed included: lignin biopolymer molecular spectra profile (peak area and height, region and baseline: ca. 1539-1504 cm-1); structural carbohydrate (STCHO, peaks area region and baseline: ca. 1485-1186 cm-1) mainly associated with hemi- and cellulosic compounds; cellulosic materials peak area (centered at ca. 1240 cm-1 with region and baseline: ca. 1272-1186 cm-1); total carbohydrate (CHO, peaks area region and baseline: ca. 1186-946 cm-1). The results showed that the functional groups (biomolecular, biopolymer) in the combined feeds are sensitive to the changes of carbohydrate chemical and nutrient profiles. The changes of the CHO molecular spectroscopic features in the combined feeds were highly correlated with CHO chemical profiles, CHO subfractions, in situ CHO rumen degradation kinetics and fermentable organic matter supply. Further study is needed to investigate possibility of using CHO molecular spectral features as a predictor to estimate nutrient availability in combined feeds for animals and quantify their relationship.

Spectral Anomalies in the 11 and 12 micron Region From the Mariner Mars 7 Infrared Spectrometer

NASA Technical Reports Server (NTRS)

Kirkland, Laurel E.; Herr, Kenneth C.

2000-01-01

Two hundred-forty infrared spectra acquired by the 1969 Mariner Mars 7 Infrared Spectrometer (IRS), spanning the wavelength region 1.8-14.4 micron (5550-690/cm), have recently been recovered and calibrated in both wavelength and intensity. An examination of these IRS spectra has revealed absorptions at 11.25 and 12.5 micron that have not previously been reported for Mars. A search of the literature and spectral data bases shows that materials that exhibit a doublet at 11.25 and 12.5 micron are rare. In this paper we examine potential causes for these features and include a detailed discussion of carbonates, goethite, CO2 ice, and water ice. CO2 ice and water ice measured in transmission do not exhibit bands that match those recorded at 11.25 and 12.5 micron for Mars, which indicates that CO2 or water ice clouds are not the source of these features. Since these bands show no clear correlation with atmospheric path length, they are most likely caused by a surface material. In the IRS database they appear to be exceptionally intense in the western part of the Hellas basin. Goethite exhibits bands that are a good spectral match, but confirming whether goethite causes the features will require additional studies of the 20-50 micron region. These studies will require laboratory measurements of weathering coatings and an examination of spectra recorded of Mars by the 1971 Mariner Mars Infrared Interferometer Spectrometer (IRIS; 5-50 micron 2000200/cm) and the 1996 Thermal Emission Spectrometer (TES; 6-50 micron 1667-200/cm).

Spectral and Geological Characterization of Beach Components in Northern Puerto Rico

NASA Astrophysics Data System (ADS)

Caraballo Álvarez, I. O.; Torres-Perez, J. L.; Barreto, M.

2015-12-01

Understanding how changes in beach components may reflect beach processes is essential since variations along beach profiles can shed light on river and ocean processes influencing beach sedimentation and beachrock formation. It is likely these influences are related to beach proximity within the Río Grande de Manatí river mouth. Therefore, this study focuses on characterizing beach components at two sites in Manatí, Puerto Rico. Playa Machuca and Playa Tombolo, which are separated by eolianites, differ greatly in sediment size, mineralogy, and beachrock morphology. Several approaches were taken to geologically and spectrally characterize main beach components at each site. These approaches included field and microscopic laboratory identification, granulometry, and a comparison between remote sensing reflectance (Rrs) obtained with a field spectroradiometer and pre-existing spectral library signatures. Preliminary results indicate a positive correlation between each method. This study may help explore the possibility of using only Rrs to characterize beach and shallow submarine components for detailed image analysis and management of coastal features.This study focuses on characterizing beach components at two sites in Manatí, Puerto Rico. Playa Machuca and Playa Tombolo, two beaches that are separated by eolianites, differ greatly in sediment size and mineralogy, as well as in beachrock morphology. Understanding how changes in beach components may reflect beach processes is essential, since it is likely that differences are mostly related to each beaches' proximity to the Río Grande de Manatí river mouth. Hence, changes in components along beach profiles can shed light on the river's and the ocean's influence on beach sedimentation and beachrock formation. Several approaches were taken to properly geologically and spectrally characterize the main beach components at each site. These approaches included field and microscopic laboratory identification, granulometry, and a comparison between remote sensing reflectance (Rrs) obtained with a field spectroradiometer and the ENVI spectral library. Preliminary results show a positive correlation between each method. This study may help explore the possibility of using only Rrs to characterize beach and shallow submarine components for detailed image analysis and management of coastal features.

Frequency Spectrum for New Aviation Data Links: Initial Study Results

NASA Technical Reports Server (NTRS)

Matolak, David W.; Branstetter, James R.

2004-01-01

We describe results from an initial study to assess the suitability of various spectral bands for supporting the deployment of new aviation data links (ADL). The study focused on systems and spectral bands that can deliver VHF data link (VDL)-or-higher data rates in a two-way communication setting, including air-ground, ground-air, and air-air modes of operation. In the first part of our paper, we briefly discuss the current situation regarding communications, navigation, and surveillance (CNS) links and existing spectrum, and the well-known need for new aviation data links. We next provide an overview of related systems, and discuss key factors involved in the use of spectrum in various bands for any future integrated CNS data link, addressing primarily the lower few layers of the communications protocol stack. Desired attributes of a new ADL system are discussed, and the beneficial aspects of a particular transmission technique spread spectrum are summarized. We also provide a short list of several example potential spectral regions, and note that while none of the existing systems will likely meet the full range of desired features of a new ADL, several systems and spectral regions offer promise in terms of one or more characteristics. A detailed discussion and evaluation of these spectral regions is proposed as future work. We include a few brief examples to illustrate initial technical results regarding spread spectrum overlay, also a subject for future work.

Semiconductor Laser Multi-Spectral Sensing and Imaging

PubMed Central

Le, Han Q.; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers. PMID:22315555

Semiconductor laser multi-spectral sensing and imaging.

PubMed

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

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.

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.

Speech Segregation based on Binary Classification

DTIC Science & Technology

2016-07-15

including the IBM, the target binary mask (TBM), the IRM, the short -time Fourier transform spectral magnitude (FFT-MAG) and its corresponding mask (FFT...complementary features and a fixed DNN as the discriminative learning machine. For evaluation metrics, besides SNR, we use the Short -Time Objective...target analysis is a recent successful intelligibility test conducted on both normal-hearing (NH) and hearing-impaired (HI) listeners. The speech

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.

Spectrophotometric Redshifts in the Faint Infrared Grism Survey: Finding Overdensities of Faint Galaxies

NASA Astrophysics Data System (ADS)

Pharo, John; Malhotra, Sangeeta; Rhoads, James; Ryan, Russell; Tilvi, Vithal; Pirzkal, Norbert; Finkelstein, Steven; Windhorst, Rogier; Grogin, Norman; Koekemoer, Anton; Zheng, Zhenya; Hathi, Nimish; Kim, Keunho; Joshi, Bhavin; Yang, Huan; Christensen, Lise; Cimatti, Andrea; Gardner, Jonathan P.; Zakamska, Nadia; Ferreras, Ignacio; Hibon, Pascale; Pasquali, Anna

2018-04-01

We improve the accuracy of photometric redshifts by including low-resolution spectral data from the G102 grism on the Hubble Space Telescope (HST), which assists in redshift determination by further constraining the shape of the broadband spectral energy distribution (SED) and identifying spectral features. The photometry used in the redshift fits includes near-infrared photometry from FIGS+CANDELS, as well as optical data from ground-based surveys and HST ACS, and mid-IR data from Spitzer. We calculated the redshifts through the comparison of measured photometry with template galaxy models, using the EAZY photometric redshift code. For objects with F105W < 26.5 AB mag with a redshift range of 0 < z < 6, we find a typical error of Δz = 0.03 ∗ (1 + z) for the purely photometric redshifts; with the addition of FIGS spectra, these become Δz = 0.02 ∗ (1 + z), an improvement of 50%. Addition of grism data also reduces the outlier rate from 8% to 7% across all fields. With the more accurate spectrophotometric redshifts (SPZs), we searched the FIGS fields for galaxy overdensities. We identified 24 overdensities across the four fields. The strongest overdensity, matching a spectroscopically identified cluster at z = 0.85, has 28 potential member galaxies, of which eight have previous spectroscopic confirmation, and features a corresponding X-ray signal. Another corresponding to a cluster at z = 1.84 has 22 members, 18 of which are spectroscopically confirmed. Additionally, we find four overdensities that are detected at an equal or higher significance in at least one metric to the two confirmed clusters.

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

Dust That's Worth Keeping

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

Hazi, A

2006-01-25

Images taken of interstellar space often display a colorful canvas of portions of the electromagnetic spectrum. Dispersed throughout the images are interstellar clouds of dust and gas--remnants ejected from stars and supernovae over billions and billions of years. For more than 40 years, astronomers have observed that interstellar dust exhibits a consistent effect at a spectral wavelength of 2,175 angstroms, the equivalent of 5.7 electronvolts in energy on the electromagnetic spectrum. At this wavelength, light from stars is absorbed by dust in the interstellar medium, blocking the stars light from reaching Earth. The 2,175-angstrom feature, which looks like a bumpmore » on spectra, is the strongest ultraviolet-visible light spectral signature of interstellar dust and is visible along nearly every observational line of sight. Scientists have sought to solve the mystery of what causes the 2,175-angstrom feature by reproducing the effect in the laboratory. They speculated a number of possibilities, including fullerenes (buckyballs), nanodiamonds, and even interstellar organisms. However, none of these materials fits the data for the unique spectral feature. Limitations in the energy and spatial resolution achievable with electron microscopes and ion microprobes--the two main instruments used to study samples of dust--have also prevented scientists from finding the answer. A collaborative effort led by Livermore physicist John Bradley and funded by the National Aeronautics and Space Administration (NASA) has used a new-generation transmission electron microscope (TEM) and nanoscale ion microprobe to unlock the mystery. The Livermore group includes physicists Zu Rong Dai, Ian Hutcheon, Peter Weber, and Sasa Bajt and postdoctoral researchers Hope Ishii, Giles Graham, and Julie Smith. They collaborated with the University of California at Davis (UCD), Lawrence Berkeley National Laboratory, Washington University's Laboratory for Space Sciences in St. Louis, and NASA's Ames Research Center for their discovery. The team analyzed micrometer-size interplanetary dust particles (IDPs), each about one-tenth the diameter of a human hair. Within the particles, they found carriers of the 2,175-angstrom feature: organic carbon mixed with amorphous silicates (glass with embedded metals and sulfides, GEMS), two of the most common materials in interstellar space. Ishii says, ''Organic carbon and amorphous silicates are abundant in interstellar dust clouds, and abundant carriers are needed to account for the frequent astronomical observation of the 2,175-angstrom feature. It makes sense that this ubiquitous feature would come from common materials in interstellar space''. The group's results increase scientific understanding of the starting materials for the formation of the Sun, solar system, and life on Earth.« less

Dust That's Worth Keeping

NASA Technical Reports Server (NTRS)

Hazi, A.

2006-01-01

Images taken of interstellar space often display a colorful canvas of portions of the electromagnetic spectrum. Dispersed throughout the images are interstellar clouds of dust and gas--remnants ejected from stars and supernovae over billions and billions of years. For more than 40 years, astronomers have observed that interstellar dust exhibits a consistent effect at a spectral wavelength of 2,175 angstroms, the equivalent of 5.7 electronvolts in energy on the electromagnetic spectrum. At this wavelength, light from stars is absorbed by dust in the interstellar medium, blocking the stars light from reaching Earth. The 2,175-angstrom feature, which looks like a bump on spectra, is the strongest ultraviolet-visible light spectral signature of interstellar dust and is visible along nearly every observational line of sight. Scientists have sought to solve the mystery of what causes the 2,175-angstrom feature by reproducing the effect in the laboratory. They speculated a number of possibilities, including fullerenes (buckyballs), nanodiamonds, and even interstellar organisms. However, none of these materials fits the data for the unique spectral feature. Limitations in the energy and spatial resolution achievable with electron microscopes and ion microprobes--the two main instruments used to study samples of dust--have also prevented scientists from finding the answer. A collaborative effort led by Livermore physicist John Bradley and funded by the National Aeronautics and Space Administration (NASA) has used a new-generation transmission electron microscope (TEM) and nanoscale ion microprobe to unlock the mystery. The Livermore group includes physicists Zu Rong Dai, Ian Hutcheon, Peter Weber, and Sasa Bajt and postdoctoral researchers Hope Ishii, Giles Graham, and Julie Smith. They collaborated with the University of California at Davis (UCD), Lawrence Berkeley National Laboratory, Washington University's Laboratory for Space Sciences in St. Louis, and NASA's Ames Research Center for their discovery. The team analyzed micrometer-size interplanetary dust particles (IDPs), each about one-tenth the diameter of a human hair. Within the particles, they found carriers of the 2,175-angstrom feature: organic carbon mixed with amorphous silicates (glass with embedded metals and sulfides, GEMS), two of the most common materials in interstellar space. Ishii says, 'Organic carbon and amorphous silicates are abundant in interstellar dust clouds, and abundant carriers are needed to account for the frequent astronomical observation of the 2,175-angstrom feature. It makes sense that this ubiquitous feature would come from common materials in interstellar space'. The group's results increase scientific understanding of the starting materials for the formation of the Sun, solar system, and life on Earth.

Faceting for direction-dependent spectral deconvolution

NASA Astrophysics Data System (ADS)

Tasse, C.; Hugo, B.; Mirmont, M.; Smirnov, O.; Atemkeng, M.; Bester, L.; Hardcastle, M. J.; Lakhoo, R.; Perkins, S.; Shimwell, T.

2018-04-01

The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the direction-dependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wideband wide-field spectral deconvolution framework (DDFacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, position-dependent Point Spread Function, etc). We discuss two wideband spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of DDFacet presented here can account for any externally defined Jones matrices and/or beam patterns.

Massively parallel sensing of trace molecules and their isotopologues with broadband subharmonic mid-infrared frequency combs

NASA Astrophysics Data System (ADS)

Muraviev, A. V.; Smolski, V. O.; Loparo, Z. E.; Vodopyanov, K. L.

2018-04-01

Mid-infrared spectroscopy offers supreme sensitivity for the detection of trace gases, solids and liquids based on tell-tale vibrational bands specific to this spectral region. Here, we present a new platform for mid-infrared dual-comb Fourier-transform spectroscopy based on a pair of ultra-broadband subharmonic optical parametric oscillators pumped by two phase-locked thulium-fibre combs. Our system provides fast (7 ms for a single interferogram), moving-parts-free, simultaneous acquisition of 350,000 spectral data points, spaced by a 115 MHz intermodal interval over the 3.1-5.5 µm spectral range. Parallel detection of 22 trace molecular species in a gas mixture, including isotopologues containing isotopes such as 13C, 18O, 17O, 15N, 34S, 33S and deuterium, with part-per-billion sensitivity and sub-Doppler resolution is demonstrated. The technique also features absolute optical frequency referencing to an atomic clock, a high degree of mutual coherence between the two mid-infrared combs with a relative comb-tooth linewidth of 25 mHz, coherent averaging and feasibility for kilohertz-scale spectral resolution.

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.

Multimodal Ultrawide-Field Imaging Features in Waardenburg Syndrome.

PubMed

Choudhry, Netan; Rao, Rajesh C

2015-06-01

A 45-year-old woman was referred for bilateral irregular fundus pigmentation. Dilated fundus examination revealed irregular hypopigmentation posterior to the equator in both eyes, confirmed by fundus autofluorescence. A thickened choroid was seen on enhanced-depth imaging spectral-domain optical coherence tomography (EDI SD-OCT). Systemic evaluation revealed sensorineural deafness, telecanthus, and a white forelock. Further investigation revealed a first-degree relative with Waardenburg syndrome. Waardenburg syndrome is characterized by a group of features including telecanthus, a broad nasal root, synophrys of the eyebrows, piedbaldism, heterochromia irides, and deafness. Choroidal hypopigmentation is a unique feature that can be visualized with ultrawide-field fundus autofluorescence. The choroid may also be thickened and its thickness measured with EDI SD-OCT. Copyright 2015, SLACK Incorporated.

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

Crown-Level Tree Species Classification Using Integrated Airborne Hyperspectral and LIDAR Remote Sensing Data

NASA Astrophysics Data System (ADS)

Wang, Z.; Wu, J.; Wang, Y.; Kong, X.; Bao, H.; Ni, Y.; Ma, L.; Jin, J.

2018-05-01

Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR) and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1) A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM) derived from LiDAR data; 2) The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3) Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4) The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90) performed better than LiDAR-metrics method (OA = 79.86 %, Kc = 0.81) and spectral-metircs method (OA = 71.26, Kc = 0.69) in terms of classification accuracy, which indicated that the advanced method of data processing and sensitive feature selection are critical for improving the accuracy of crown-level tree species classification.

The study of active tectonic based on hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Cui, J.; Zhang, S.; Zhang, J.; Shen, X.; Ding, R.; Xu, S.

2017-12-01

As of the latest technical methods, hyperspectral remote sensing technology has been widely used in each brach of the geosciences. However, it is still a blank for using the hyperspectral remote sensing to study the active structrure. Hyperspectral remote sensing, with high spectral resolution, continuous spectrum, continuous spatial data, low cost, etc, has great potentialities in the areas of stratum division and fault identification. Blind fault identification in plains and invisible fault discrimination in loess strata are the two hot problems in the current active fault research. Thus, the study of active fault based on the hyperspectral technology has great theoretical significance and practical value. Magnetic susceptibility (MS) records could reflect the rhythm alteration of the formation. Previous study shown that MS has correlation with spectral feature. In this study, the Emaokou section, located to the northwest of the town of Huairen, in Shanxi Province, has been chosen for invisible fault study. We collected data from the Emaokou section, including spectral data, hyperspectral image, MS data. MS models based on spectral features were established and applied to the UHD185 image for MS mapping. The results shown that MS map corresponded well to the loess sequences. It can recognize the stratum which can not identity by naked eyes. Invisible fault has been found in this section, which is useful for paleoearthquake analysis. The faults act as the conduit for migration of terrestrial gases, the fault zones, especially the structurally weak zones such as inrtersections or bends of fault, may has different material composition. We take Xiadian fault for study. Several samples cross-fault were collected and these samples were measured by ASD Field Spec 3 spectrometer. Spectral classification method has been used for spectral analysis, we found that the spectrum of the fault zone have four special spectral region(550-580nm, 600-700nm, 700-800nm and 800-900nm), which different with the spectrum of the none-fault zone. It could help us welly located the fault zone. The located result correspond well to the physical prospecting method result. The above study shown that Hypersepctral remote sensing technology provide a new method for active study.

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.

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.

A conjunct near-surface spectroscopy system for fix-angle and multi-angle continuous measurements of canopy reflectance and sun-induced chlorophyll fluorescence

NASA Astrophysics Data System (ADS)

Zhang, Qian; Fan, Yifeng; Zhang, Yongguang; Chou, Shuren; Ju, Weimin; Chen, Jing M.

2016-09-01

An automated spectroscopy system, which is divided into fix-angle and multi-angle subsystems, for collecting simultaneous, continuous and long-term measurements of canopy hyper-spectra in a crop ecosystem is developed. The fix-angle subsystem equips two spectrometers: one is HR2000+ (OceanOptics) covering the spectral range 200-1100 nm with 1.0 nm spectral resolution, and another one is QE65PRO (OceanOptics) providing 0.1 nm spectral resolution within the 730-780 nm spectral range. Both spectrometers connect a cosine-corrected fiber-optic fixed up-looking to collect the down-welling irradiance and a bare fiber-optic to measure the up-welling radiance from the vegetation. An inline fiber-optic shutter FOS-2x2-TTL (OceanOptics) is used to switch between input fibers to collect the signal from either the canopy or sky at one time. QE65PRO is used to permit estimation of vegetation Sun-Induced Fluorescence (SIF) in the O2-A band. The data collection scheme includes optimization of spectrometer integration time to maximize the signal to noise ratio and measurement of instrument dark currency. The multi-angle subsystem, which can help understanding bidirectional reflectance effects, alternatively use HR4000 (OceanOptics) providing 0.1 nm spectral resolution within the 680-800 nm spectral range to measure multi-angle SIF. This subsystem additionally includes a spectrometer Unispec-DC (PPSystems) featuring both up-welling and down-welling channels with 3 nm spectral resolution covering the 300-1100 nm spectral range. Two down-looking fiber-optics are mounted on a rotating device PTU-D46 (FLIR Systems), which can rotate horizontally and vertically at 10° angular step widths. Observations can be used to calculate canopy reflectance, vegetation indices and SIF for monitoring plant physiological processes.

Spectral Confusion for Cosmological Surveys of Redshifted C II Emission

NASA Technical Reports Server (NTRS)

Kogut, A.; Dwek, E.; Moseley, S. H.

2015-01-01

Far-infrared cooling lines are ubiquitous features in the spectra of star-forming galaxies. Surveys of redshifted fine-structure lines provide a promising new tool to study structure formation and galactic evolution at redshifts including the epoch of reionization as well as the peak of star formation. Unlike neutral hydrogen surveys, where the 21 cm line is the only bright line, surveys of redshifted fine-structure lines suffer from confusion generated by line broadening, spectral overlap of different lines, and the crowding of sources with redshift. We use simulations to investigate the resulting spectral confusion and derive observing parameters to minimize these effects in pencilbeam surveys of redshifted far-IR line emission. We generate simulated spectra of the 17 brightest far-IR lines in galaxies, covering the 150-1300 µm wavelength region corresponding to redshifts 0 < z < 7, and develop a simple iterative algorithm that successfully identifies the 158 µm [C II] line and other lines. Although the [C II] line is a principal coolant for the interstellar medium, the assumption that the brightest observed lines in a given line of sight are always [C II] lines is a poor approximation to the simulated spectra once other lines are included. Blind line identification requires detection of fainter companion lines from the same host galaxies, driving survey sensitivity requirements. The observations require moderate spectral resolution 700 < R < 4000 with angular resolution between 20? and 10', sufficiently narrow to minimize confusion yet sufficiently large to include a statistically meaningful number of sources.

Observations of rock spectral classes by the Opportunity rover's Pancam on northern Cape York and on Matijevic Hill, Endeavour Crater, Mars

NASA Astrophysics Data System (ADS)

Farrand, W. H.; Bell, J. F.; Johnson, J. R.; Rice, M. S.; Jolliff, B. L.; Arvidson, R. E.

2014-11-01

The Opportunity rover's exploration of the portion of the rim of Endeavour crater known as Cape York included examination of the sulfate-bearing Grasberg formation and the Matijevic Hill region. Multispectral visible and near-infrared (VNIR) Pancam observations were used to characterize reflectance properties of rock units. Using spectral end-member detection and classification approaches including a principal components/n-dimensional visualization, automatic sequential maximum angle convex cone method, and classification through hierarchical clustering, six main spectral classes of rock surfaces were identified: light-toned veins, Grasberg fm., the smectite-bearing Matijevic formation, the hematitic "blueberry" spherules, resistant spherules within the Matijevic fm. dubbed "newberries," and the Shoemaker formation impact breccia. Some of these could be divided into spectral subclasses. There were three types of veins: veins in the bench unit of Cape York, thinner veins in the Matijevic fm., and boxwork pattern-forming veins. The bench unit veins had higher 535 nm band depths than the other two vein subclasses and a steeper 934 to 1009 nm slope. The Grasberg fm. has VNIR spectral features that are interpreted to indicate higher fractions of red hematite than in the sulfate-bearing Burns Fm. The Matijevic fm. includes both light-toned, fine-grained matrix, and dark-toned veneers. The latter has a weak near-infrared absorption band centered near 950 nm consistent with nontronite. Observations of Rock Abrasion Tool brushed and ground newberries indicated that cuttings from the RAT grind had a longer wavelength reflectance maximum and deeper 535 nm band depth, consistent with more oxidized materials. Greater oxidation of cementing materials in the newberries is consistent with a diagenetic concretion origin.

Symmetry breaking, mixing, instability, and low-frequency variability in a minimal Lorenz-like system.

PubMed

Lucarini, Valerio; Fraedrich, Klaus

2009-08-01

Starting from the classical Saltzman two-dimensional convection equations, we derive via a severe spectral truncation a minimal 10 ODE system which includes the thermal effect of viscous dissipation. Neglecting this process leads to a dynamical system which includes a decoupled generalized Lorenz system. The consideration of this process breaks an important symmetry and couples the dynamics of fast and slow variables, with the ensuing modifications to the structural properties of the attractor and of the spectral features. When the relevant nondimensional number (Eckert number Ec) is different from zero, an additional time scale of O(Ec(-1)) is introduced in the system, as shown with standard multiscale analysis and made clear by several numerical evidences. Moreover, the system is ergodic and hyperbolic, the slow variables feature long-term memory with 1/f(3/2) power spectra, and the fast variables feature amplitude modulation. Increasing the strength of the thermal-viscous feedback has a stabilizing effect, as both the metric entropy and the Kaplan-Yorke attractor dimension decrease monotonically with Ec. The analyzed system features very rich dynamics: it overcomes some of the limitations of the Lorenz system and might have prototypical value in relevant processes in complex systems dynamics, such as the interaction between slow and fast variables, the presence of long-term memory, and the associated extreme value statistics. This analysis shows how neglecting the coupling of slow and fast variables only on the basis of scale analysis can be catastrophic. In fact, this leads to spurious invariances that affect essential dynamical properties (ergodicity, hyperbolicity) and that cause the model losing ability in describing intrinsically multiscale processes.

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

Early pest detection in soy plantations from hyperspectral measurements: a case study for caterpillar detection

NASA Astrophysics Data System (ADS)

Tailanián, Matías; Castiglioni, Enrique; Musé, Pablo; Fernández Flores, Germán.; Lema, Gabriel; Mastrángelo, Pedro; Almansa, Mónica; Fernández Liñares, Ignacio; Fernández Liñares, Germán.

2015-10-01

Soybean producers suffer from caterpillar damage in many areas of the world. Estimated average economic losses are annually 500 million USD in Brazil, Argentina, Paraguay and Uruguay. Designing efficient pest control management using selective and targeted pesticide applications is extremely important both from economic and environmental perspectives. With that in mind, we conducted a research program during the 2013-2014 and 2014-2015 planting seasons in a 4,000 ha soybean farm, seeking to achieve early pest detection. Nowadays pest presence is evaluated using manual, labor-intensive counting methods based on sampling strategies which are time consuming and imprecise. The experiment was conducted as follows. Using manual counting methods as ground-truth, a spectrometer capturing reflectance from 400 to 1100 nm was used to measure the reflectance of soy plants. A first conclusion, resulting from measuring the spectral response at leaves level, showed that stress was a property of plants since different leaves with different levels of damage yielded the same spectral response. Then, to assess the applicability of unsupervised classification of plants as healthy, biotic-stressed or abiotic-stressed, feature extraction and selection from leaves spectral signatures, combined with a Supported Vector Machine classifier was designed. Optimization of SVM parameters using grid search with cross-validation, along with classification evaluation by ten-folds cross-validation showed a correct classification rate of 95%, consistently on both seasons. Controlled experiments using cages with different numbers of caterpillars--including caterpillar-free plants--were also conducted to evaluate consistency in trends of the spectral response as well as the extracted features.

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.

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

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).

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.

Spectroscopic Methods of Remote Sensing for Vegetation Characterization

NASA Astrophysics Data System (ADS)

Kokaly, R. F.

2013-12-01

Imaging spectroscopy (IS), often referred to as hyperspectral remote sensing, is one of the latest innovations in a very long history of spectroscopy. Spectroscopic methods have been used for understanding the composition of the world around us, as well as, the solar system and distant parts of the universe. Continuous sampling of the electromagnetic spectrum in narrow bands is what separates IS from previous forms of remote sensing. Terrestrial imaging spectrometers often have hundreds of channels that cover the wavelength range of reflected solar radiation, including the visible, near-infrared (NIR), and shortwave infrared (SWIR) regions. In part due to the large number of channels, a wide variety of methods have been applied to extract information from IS data sets. These can be grouped into several broad classes, including: multi-channel indices, statistical procedures, full spectrum mixing models, and spectroscopic methods. Spectroscopic methods carry on the more than 150 year history of laboratory-based spectroscopy applied to material identification and characterization. Spectroscopic methods of IS relate the positions and shapes of spectral features resolved by airborne and spaceborne sensors to the biochemical and physical composition of vegetation in a pixel. The chlorophyll 680nm, water 980nm, water 1200nm, SWIR 1700nm, SWIR 2100nm, and SWIR 2300nm features have been the subject of study. Spectral feature analysis (SFA) involves isolating such an absorption feature using continuum removal (CR) and calculating descriptors of the feature, such as center position, depth, width, area, and asymmetry. SFA has been applied to quantify pigment and non-pigment biochemical concentrations in leaves, plants, and canopies. Spectral feature comparison (SFC) utilizes CR of features in each pixel's spectrum and linear regression with continuum-removed features in reference spectra in a library of known vegetation types to map vegetation species and communities. SFC has been applied to map the distributions of minerals in soils and rocks; however, its application to characterize vegetation cover has been less widespread than SFA. Using IS data and the USGS Processing Routines in IDL for Spectroscopic Measurements (PRISM; http://pubs.usgs.gov/of/2011/1155/), this talk will examine requirements for and limitations in applying SFA and SFC to characterize vegetation. A time series of Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) data collected in the marshes of Louisiana following the Deepwater Horizon oil spill will be used to examine the impact of varying leaf water content on the shapes of the SWIR 1700, 2100, and 2300 nm features and the implications of these changes on vegetation identification and biochemical estimation. The USGS collection of HyMap data over Afghanistan, the largest terrestrial coverage of IS data to date, will be used to demonstrate the characterization of vegetation in arid and semi-arid regions, in which chlorophyll absorption is often weak and soil and rock mineral absorption features overlap vegetation features. Hyperion data, overlapping the HyMap data, will be presented to illustrate the complications that arise when signal-to-noise is low. The benefits of and challenges to applying a spectroscopic remote sensing approach to imaging spectrometer data will be discussed.

Why we need detailed visible-range spectral data on Kuiper belt objects?

NASA Astrophysics Data System (ADS)

Busarev, V. V.

2001-05-01

Our understanding of Kuiper belt objects (KBOs)' nature may be based on two general scenarios of their origin. First, they could result from early accretional phases of the Solar System ``in situ". Then they are probably the most primitive and unprocessed bodies among known and should be mostly icy, with a very low content of silicate component. Second, a considerable portion of them (if not a majority) might have been thrown by Jupiter and other giant planets from their zones of accumulation. If so, they could include much more silicates (possibly up to 40%). To check the suppositions we need high-resolution visible and near-infrared spectral data on Centaurs (as possible `fugitives' from the Kuiper belt) and the KBOs. Because of faintness of the objects their physicochemical properties remain still little-known. Visible-range observations of the bodies by means of a spacecraft approaching to the belt could much help in solving the problem. Visible-infrared spectrophotometric observations of the objects showed a considerable diversity among them (Jewitt D. & J. Luu, 1998, Astron. J., 115, 1667-1670). It hints at a diversity in content of their matter. Spectral features of ices could not probably dominate in the visible range spectra of silicate-bearing KBOs. Reflectance spectra of principal gases' frosts are mainly flat and featureless in the range (Wagner J. K. et al., 1987, Icarus, 69, 14-28). Besides, silicates of KBOs are probably oxidized and hydrated to a high extent. Highly hydrated main-belt C-class asteroids have absorption bands at 0.43 and 0.6-0.8 microns (up to about 5%) (Vilas F. & M. J. Gaffey, 1989, Science, 246, 790-792 and Vilas F. et al., 1993, Icarus, 102, 225-231). Similar spectral features attributed to oxidized and hydrated silicates were also found on many M- and S-asteroids (e. g., Busarev V. V., 2001, LPSC XXXII, abstract 1927). The absorption bands are interpreted as caused by electronic processes in a bulk of oxidized silicates and hydrated clay minerals including structural OH-groups. Thus, the absorption features may be considered as indicators of a presence of oxidized and/or hydrated silicates on a solid body regardless of its position in the Solar System. For these reasons we have started visible-range spectroscopic observations of Centaurs and the KBOs on Russian 6-m telescope.

Mid-infrared spectroscopy to better characterize icy moon surface compositions

NASA Astrophysics Data System (ADS)

Young, Cindy L.; Wray, James J.; Hand, Kevin P.; Poston, Michael; Carlson, Robert W.; Clark, Roger Nelson; Spencer, John R.; Jennings, Donald

2016-10-01

Previous spectroscopy work on icy moons has focused primarily on the visible and near-IR portion of the spectrum due to challenges presented by a low signal to noise ratio at the longer wavelengths. However, the mid-IR is the region of the strongest fundamental vibrations of many important types of molecules (e.g., organics) and has the potential to reveal unique compositional information [1]. We use the wealth of data that is now available from Cassini's Composite Infrared Spectrometer (CIRS) to average spectra over similar regions to improve the signal to noise, helping to reveal spectral features never before observed.Our initial work has already led to the detection and tentative laboratory identification of the first spectral features observed for any icy moon in the mid-IR [2]. On Iapetus' dark terrain, we found an emissivity feature at ~855 cm-1 and a possible doublet at 660 and 690 cm-1 that does not correspond to any known instrument artifacts. We attributed the 855 cm-1 feature to fine-grained silicates, similar to those found in dust on Mars and in meteorites, which are nearly featureless at shorter wavelengths [e.g., 3, 4]. Silicates on the dark terrains of Saturn's icy moons have been suspected for decades, but there have been no definitive detections until this work.We measured the vacuum, low temperature mid-IR spectra of various fine-grained powdered silicates, including Mg-rich serpentines, often present in meteorites. Some of these materials do have emissivity features near 855 cm-1 and exhibit a doublet. Presently, we are continuing to comb the CIRS icy moon database for spectral features (particularly focusing on the warmer surfaces in the Saturn system) and are performing further vacuum chamber measurements to experiment with more sample types and ice/sample mixtures to determine the impacts of changing conditions in the chamber on features. We are also working to understand how surface porosity and mixing with various darkening agents may impact our spectra.[1] Flasar, F. M., et al. (2004), Space Sci Rev, 115, 169.[2] Young, C. L., et al. (2015), ApJ Lett., 811, L27.[3] Christensen, P. R., et al. (2004), Sci, 306, 1733.[4] McAdam, M. M., et al. (2015), Icar, 245, 320.

Mineralogy of dark asteroids: Detection of phyllosilicate features in the mid-infrared

NASA Astrophysics Data System (ADS)

McAdam, Margaret; Sunshine , Jessica Sunshine M.; Kelley, Michael S.

2014-11-01

Dark asteroids (C- and related types) have been shown to have phyllosilicates on their surfaces by the presence of the 0.7-µm charge transfer band in the visible/near-infrared (VIS/NIR) spectral region (e.g. [1], [2]). Observations of asteroids in the 2.5-5-µm have also indicated the presence of water [3, 4] and phyllosilicates [5, 6]. Phyllosilicates also have spectral features in the 8-30-µm [7]. The results of a coordinated spectral-mineralogical study of aqueously altered meteorites [8] can be used to both remotely identify the presence of aqueous alteration and determine the degree of alteration on asteroids. Two main regions have strong features related to the mineralogy and degree of alteration: the 10-13-µm and the 16-25-µm region. Alteration features change continuously in these regions between less 60%) and highly 90%) altered meteorites. These features have been identified in the spectra of some dark asteroids [8, 9, 10]. Additionally, no trends are found between 0.7-µm charge transfer band and degree of alteration. While all meteorites with a 0.7-µm band have phyllosilicates, the absence of a 0.7-µm band is not indicative of the absence of alteration. Altered meteorites always exhibit MIR features that are directly related to their degree of alteration whether or not they have a 0.7-µm band. Here, we present preliminary results of a survey of archived Spitzer Space Telescope data of asteroids in the 10-13-µm region and the 16-25-µm region (where data is available) including comparisons to published VIS/NIR spectra of the same dark asteroids without VIS/NIR features. Possible effects in comparing laboratory measurements of meteorite powders under ambient conditions to telescopic spectra of asteroid regoliths are considered. [1] Vilas and Gaffey, (1989) Nature, 246, 790-792. [2] Barucci et al (1998) Icarus, 132, 388-396. [3] Campins et al., (2010), Nature Letters, 464, 1320-1321. [4] Rivkin & Emery (2010) Nature Letters, 464, 1322-1323. [5] Hargrove, et al. (2012), Icarus, 221, 453-455. [6] Takir and Emery (2012) Icarus, 219, 641-654. [7] Calvin & King, (1997), Met. & Plan. Sci., 32, 693-701. [8] McAdam et al, Icarus, in review. [9] McAdam, et al (2013) DPS abs. [10] McAdam et al, ACM abs.

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.

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...

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

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

DoE Phase II SBIR: Spectrally-Assisted Vehicle Tracking

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

Villeneuve, Pierre V.

2013-02-28

The goal of this Phase II SBIR is to develop a prototype software package to demonstrate spectrally-aided vehicle tracking performance. The primary application is to demonstrate improved target vehicle tracking performance in complex environments where traditional spatial tracker systems may show reduced performance. Example scenarios in Figure 1 include a) the target vehicle obscured by a large structure for an extended period of time, or b), the target engaging in extreme maneuvers amongst other civilian vehicles. The target information derived from spatial processing is unable to differentiate between the green versus the red vehicle. Spectral signature exploitation enables comparison ofmore » new candidate targets with existing track signatures. The ambiguity in this confusing scenario is resolved by folding spectral analysis results into each target nomination and association processes. Figure 3 shows a number of example spectral signatures from a variety of natural and man-made materials. The work performed over the two-year effort was divided into three general areas: algorithm refinement, software prototype development, and prototype performance demonstration. The tasks performed under this Phase II to accomplish the program goals were as follows: 1. Acquire relevant vehicle target datasets to support prototype. 2. Refine algorithms for target spectral feature exploitation. 3. Implement a prototype multi-hypothesis target tracking software package. 4. Demonstrate and quantify tracking performance using relevant data.« less

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance

PubMed Central

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2017-01-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), Scdm (units: nm−1), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving Scdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360–500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of Scdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors. PMID:29201583

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance.

PubMed

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2016-03-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), S cdm (units: nm -1 ), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving S cdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360-500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of S cdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors.

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.

Spectroscopy of asteroids in unusual orbits

NASA Technical Reports Server (NTRS)

Cochran, W. D.; Cochran, A. L.; Barker, E. S.

1986-01-01

Medium-resolution spectroscopy of a collection of nonmain-belt asteroids has been obtained in order to search for possible cometlike spectral features. The asteroids include nine earth approachers, two Trojans, and the unusual object 2060 Chiron. All spectra were obtained and reduced in the same manner as comet data in the McDonald Observatory Faint Comet Survey. No indication of cometary activity was found in any of the asteroids observed.

A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

USGS Publications Warehouse

Maxwell, S.K.; Schmidt, Gail L.; Storey, James C.

2007-01-01

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

NASA Technical Reports Server (NTRS)

Thompson, David R.; Mandrake, Lukas; Green, Robert O.

2013-01-01

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

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.

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.

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...

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.

Poster 2:Ab initio calculations of low temperature hydrocarbon spectra for astrophysics: application to the modeling of methane absorption in the Titan atmosphere in a wide IR range

NASA Astrophysics Data System (ADS)

Rey, Michael; Nikitin, Andrei; Bezard, Bruno; Rannou, Pascal; Coustenis, Athena; Tyuterev, Vladimir

2016-06-01

Knowledge of intensities of spectral transitions in various temperature ranges including very low-T conditions is essential for the modeling of optical properties of planetary atmospheres and for other astrophysical applications. The temperature dependence of spectral features is crucial, but quantified experimental information in a wide spectral range is generally missing. A significant progress has been recently achieved in first principles quantum mechanical predictions (ab initio electronic structure + variational nuclear motion calculations) of rotationally resolved spectra for hydrocarbon molecules such as methane , ethylene and their isotopic species [1,2] . We have recently reported the TheoReTS information system (theorets.univ-reims.fr, theorets.tsu.ru) for theoretical spectra based on variational predictions from molecular potential energy and dipole moment surfaces [3] that permits online simulation of radiative properties including low-T conditions of cold planets. In this work, we apply ab initio predictions of the spectra of methane isotopologues down to T=80 K for the modeling of the transmittance in the atmosphere of Titan, Saturn's largest satellite explored by the Cassini-Huygens space mission. A very good agreement over the whole infrared range from 6,000 to 11,000 cm-1 compared with observations obtained by the Descent Imager / Spectral Radiometer (DISR) on the Huygens probe [4,5] at various altitudes will be reported.

Nanophotonics-enabled smart windows, buildings and wearables

NASA Astrophysics Data System (ADS)

Smith, Geoff; Gentle, Angus; Arnold, Matthew; Cortie, Michael

2016-06-01

Design and production of spectrally smart windows, walls, roofs and fabrics has a long history, which includes early examples of applied nanophotonics. Evolving nanoscience has a special role to play as it provides the means to improve the functionality of these everyday materials. Improvement in the quality of human experience in any location at any time of year is the goal. Energy savings, thermal and visual comfort indoors and outdoors, visual experience, air quality and better health are all made possible by materials, whose "smartness" is aimed at designed responses to environmental energy flows. The spectral and angle of incidence responses of these nanomaterials must thus take account of the spectral and directional aspects of solar energy and of atmospheric thermal radiation plus the visible and color sensitivity of the human eye. The structures required may use resonant absorption, multilayer stacks, optical anisotropy and scattering to achieve their functionality. These structures are, in turn, constructed out of particles, columns, ultrathin layers, voids, wires, pure and doped oxides, metals, polymers or transparent conductors (TCs). The need to cater for wavelengths stretching from 0.3 to 35 μm including ultraviolet-visible, near-infrared (IR) and thermal or Planck radiation, with a spectrally and directionally complex atmosphere, and both being dynamic, means that hierarchical and graded nanostructures often feature. Nature has evolved to deal with the same energy flows, so biomimicry is sometimes a useful guide.

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.

The spectrum of comet austin from 910 to 1180 a.

PubMed

Green, J C; Cash, W; Cook, T A; Stern, S A

1991-01-25

A spectrum of comet Austin (1988 c(1)) has been obtained from 910 to 1180 A. Three bright emission lines were detected, including a forbidden oxygen line (1128 A), which are attributable to radiative pumping of neutral oxygen by solar Lyman beta. The relative strengths of the observed features should prove to be a useful diagnostic of the physical conditions and radiation fields in cometary comae. In addition, the absence of strong spectral features from highly volatile species such as He, Ar, or N(2) can be used to place constraints on the thermal environment under which the comet was formed and has been processed.

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.

VizieR Online Data Catalog: R absolute magnitudes of Kuiper Belt objects (Peixinho+, 2012)

NASA Astrophysics Data System (ADS)

Peixinho, N.; Delsanti, A.; Guilbert-Lepoutre, A.; Gafeira, R.; Lacerda, P.

2012-06-01

Compilation of absolute magnitude HRα, B-R color spectral features used in this work. For each object, we computed the average color index from the different papers presenting data obtained simultaneously in B and R bands (e.g. contiguous observations within a same night). When individual R apparent magnitude and date were available, we computed the HRα=R-5log(r Delta), where R is the R-band magnitude, r and Delta are the helio- and geocentric distances at the time of observation in AU, respectively. When V and V-R colors were available, we derived an R and then HRα value. We did not correct for the phase-angle α effect. This table includes also spectral information on the presence of water ice, methanol, methane, or confirmed featureless spectra, as available in the literature. We highlight only the cases with clear bands in the spectrum, which were reported/confirmed by some other work. The 1st column indicates the object identification number and name or provisional designation; the 2nd column indicates the dynamical class; the 3rd column indicates the average HRα value and 1-σ error bars; the 4th column indicates the average $B-R$ color and 1-σ error bars; the 5th column indicates the most important spectral features detected; and the 6th column points to the bibliographic references used for each object. (3 data files).

[Analysis of different health status based on characteristics of the facial spectrum photometric color].

PubMed

Xu, Jiatuo; Wu, Hongjin; Lu, Luming; Tu, Liping; Zhang, Zhifeng; Chen, Xiao

2012-12-01

This paper is aimed to observe the difference of facial color of people with different health status by spectral photometric color measuring technique according to the theory of facial color diagnosis in Internal Classic. We gathered the facial color information about the health status of persons in healthy group (183), sub-healthy group (287) and disease group (370) respectively. The information included L, a, b, C values and reflection of different wavelengths in 400-700nm with CM-2600D spectral photometric color measuring instrument on 8 points. The results indicated that overall complexion color values of the people in the three groups were significantly different. The persons in the disease group looked deep dark in features. The people in the sub-healthy group looked pale in features. The loci L, a, b, C values were with varying degrees of significant differences (P < 0.05) at 6 points among the groups, and the central position of the face in all the groups was the position with most significant differences. Comparing the facial color information at the same point of the people in the three groups, we obtained each group's diagnostic special point. There existed diagnostic values in distinguishing disease status and various status of health in some degree by spectral photometric color measuring technique. The present method provides a prosperous quantitative basis for Chinese medical inspection of the complexion diagnosis.

Deep learning with convolutional neural networks for EEG decoding and visualization

PubMed Central

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

Deep learning with convolutional neural networks for EEG decoding and visualization.

PubMed

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Automated Detection of Epileptic Biomarkers in Resting-State Interictal MEG Data

PubMed Central

Soriano, Miguel C.; Niso, Guiomar; Clements, Jillian; Ortín, Silvia; Carrasco, Sira; Gudín, María; Mirasso, Claudio R.; Pereda, Ernesto

2017-01-01

Certain differences between brain networks of healthy and epilectic subjects have been reported even during the interictal activity, in which no epileptic seizures occur. Here, magnetoencephalography (MEG) data recorded in the resting state is used to discriminate between healthy subjects and patients with either idiopathic generalized epilepsy or frontal focal epilepsy. Signal features extracted from interictal periods without any epileptiform activity are used to train a machine learning algorithm to draw a diagnosis. This is potentially relevant to patients without frequent or easily detectable spikes. To analyze the data, we use an up-to-date machine learning algorithm and explore the benefits of including different features obtained from the MEG data as inputs to the algorithm. We find that the relative power spectral density of the MEG time-series is sufficient to distinguish between healthy and epileptic subjects with a high prediction accuracy. We also find that a combination of features such as the phase-locked value and the relative power spectral density allow to discriminate generalized and focal epilepsy, when these features are calculated over a filtered version of the signals in certain frequency bands. Machine learning algorithms are currently being applied to the analysis and classification of brain signals. It is, however, less evident to identify the proper features of these signals that are prone to be used in such machine learning algorithms. Here, we evaluate the influence of the input feature selection on a clinical scenario to distinguish between healthy and epileptic subjects. Our results indicate that such distinction is possible with a high accuracy (86%), allowing the discrimination between idiopathic generalized and frontal focal epilepsy types. PMID:28713260

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.

Using the ``blue spike'' to characterize biomass-burning sites during Southern African Regional Science Initiative (SAFARI) 2000

NASA Astrophysics Data System (ADS)

McCourt, M. L.; McMillan, W. W.; Ackerman, S.; Holz, R.; Revercomb, H. E.; Tobin, D.

2004-10-01

During several flights of the ER-2 while participating in the Southern African Regional Science Initiative (SAFARI 2000), the University of Wisconsin-Madison's Scanning High Resolution Interferometer Sounder (S-HIS) obtained spectra containing isolated fires within its field of view (FOV). These fire-laden FOVs contain a spectral feature caused by rotational hot band transitions of CO2 near 2400 cm-1. Because of its location on the blue side of the 4.3 μm band of CO2, this feature is commonly referred to as the "blue spike." Using this feature, we detected fires on four flights: 24 and 27 August and 6 and 7 September 2000. Fire locations are further verified by the ER-2 pilot's flight logs and elevated brightness temperatures in the thermal detectors of the MODIS Airborne Simulator (MAS) also on board the ER-2. Using line-by-line radiative transfer calculations (Genln2) with corrections for a fire's extreme high temperatures (HiTemp), we model S-HIS spectra for various scenes: background (cool surface and cool atmosphere), smoldering (warm surface and cool atmosphere), hot gas layer (cool surface and warm atmosphere), and fire (hot surface and hot atmosphere) cases. Using the controlled burn in the Timbavati Game Reserve on 7 September 2000 as a test case, we spectrally modeled the blue spike feature seen in the spectra obtained by S-HIS while the ER-2 flew over the fire. For this case, we found that ˜4.12 ± 0.05% of the FOV contained the hot gas layer while ˜0.23 ± 0.05% was actively burning. Originally viewed as a straightforward task of using the blue spike to characterize the fire temperature and size (fraction of S-HIS FOV), our analysis shows that numerous variables, including amount of carbon dioxide, amount of water vapor, and the temperature near the fire, play significant roles in the blue spike's shape and spectral position.

Fusing Panchromatic and SWIR Bands Based on Cnn - a Preliminary Study Over WORLDVIEW-3 Datasets

NASA Astrophysics Data System (ADS)

Guo, M.; Ma, H.; Bao, Y.; Wang, L.

2018-04-01

The traditional fusion methods are based on the fact that the spectral ranges of the Panchromatic (PAN) and multispectral bands (MS) are almost overlapping. In this paper, we propose a new pan-sharpening method for the fusion of PAN and SWIR (short-wave infrared) bands, whose spectral coverages are not overlapping. This problem is addressed with a convolutional neural network (CNN), which is trained by WorldView-3 dataset. CNN can learn the complex relationship among bands, and thus alleviate spectral distortion. Consequently, in our network, we use the simple three-layer basic architecture with 16 × 16 kernels to conduct the experiment. Every layer use different receptive field. The first two layers compute 512 feature maps by using the 16 × 16 and 1 × 1 receptive field respectively and the third layer with a 8 × 8 receptive field. The fusion results are optimized by continuous training. As for assessment, four evaluation indexes including Entropy, CC, SAM and UIQI are selected built on subjective visual effect and quantitative evaluation. The preliminary experimental results demonstrate that the fusion algorithms can effectively enhance the spatial information. Unfortunately, the fusion image has spectral distortion, it cannot maintain the spectral information of the SWIR image.

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.

Artifacts reduction in VIR/Dawn data.

PubMed

Carrozzo, F G; Raponi, A; De Sanctis, M C; Ammannito, E; Giardino, M; D'Aversa, E; Fonte, S; Tosi, F

2016-12-01

Remote sensing images are generally affected by different types of noise that degrade the quality of the spectral data (i.e., stripes and spikes). Hyperspectral images returned by a Visible and InfraRed (VIR) spectrometer onboard the NASA Dawn mission exhibit residual systematic artifacts. VIR is an imaging spectrometer coupling high spectral and spatial resolutions in the visible and infrared spectral domain (0.25-5.0 μm). VIR data present one type of noise that may mask or distort real features (i.e., spikes and stripes), which may lead to misinterpretation of the surface composition. This paper presents a technique for the minimization of artifacts in VIR data that include a new instrument response function combining ground and in-flight radiometric measurements, correction of spectral spikes, odd-even band effects, systematic vertical stripes, high-frequency noise, and comparison with ground telescopic spectra of Vesta and Ceres. We developed a correction of artifacts in a two steps process: creation of the artifacts matrix and application of the same matrix to the VIR dataset. In the approach presented here, a polynomial function is used to fit the high frequency variations. After applying these corrections, the resulting spectra show improvements of the quality of the data. The new calibrated data enhance the significance of results from the spectral analysis of Vesta and Ceres.

Land surface temperature measurements from EOS MODIS data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1995-01-01

A significant progress has been made in TIR instrumentation which is required to establish the spectral BRDF/emissivity knowledge base of land-surface materials and to validate the land-surface temperature (LST) algorithms. The SIBRE (spectral Infrared Bidirectional Reflectance and Emissivity) system and a TIR system for measuring spectral directional-hemispherical emissivity have been completed and tested successfully. Optical properties and performance features of key components (including spectrometer, and TIR source) of these systems have been characterized by integrated use of local standards (blackbody and reference plates). The stabilization of the spectrometer performance was improved by a custom designed and built liquid cooling system. Methods and procedures for measuring spectral TIR BRDF and directional-hemispheric emissivity with these two systems have been verified in sample measurements. These TIR instruments have been used in the laboratory and the field, giving very promising results. The measured spectral emissivities of water surface are very close to the calculated values based on well established water refractive index values in published papers. Preliminary results show that the TIR instruments can be used for validation of the MODIS LST algorithm in homogeneous test sites. The beta-3 version of the MODIS LST software is being prepared for its delivery scheduled in the early second half of this year.

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.

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.

Reflectance spectroscopy of oxalate minerals and relevance to Solar System carbon inventories

NASA Astrophysics Data System (ADS)

Applin, Daniel M.; Izawa, Matthew R. M.; Cloutis, Edward A.

2016-11-01

The diversity of oxalate formation mechanisms suggests that significant concentrations of oxalic acid and oxalate minerals could be widely distributed in the Solar System. We have carried out a systematic study of the reflectance spectra of oxalate minerals and oxalic acid, covering the 0.2-16 μm wavelength region. Our analyses show that oxalates exhibit unique spectral features that enable discrimination between oxalate phases and from other commonly occurring compounds, including carbonates, in all regions of the spectrum except for the visible. Using these spectral data, we consider the possible contribution of oxalate minerals to previously observed reflectance spectra of many objects throughout the Solar System, including satellites, comets, and asteroids. We find that polycarboxylic acid dimers and their salts may explain the reflectance spectra of many carbonaceous asteroids in the 3 μm spectral region. We suggest surface concentration of these compounds may be a type of space weathering from the photochemical and oxidative decomposition of the organic macromolecular material found in carbonaceous chondrites. The stability and ubiquity of these minerals on Earth, in extraterrestrial materials, and in association with biological processes make them useful for many applications in Earth and planetary sciences.

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.

Characterizing Pale Blue Dots Around FGKM Stars

NASA Astrophysics Data System (ADS)

Rugheimer, S.; Kaltenegger, L.; Sasselov, D. D.; Segura, A.

2015-12-01

Exoplanet characterization of small rocky worlds will be a main focus in the coming decades. For future telescopes like JWST and UVOIR/HDST, an exoplanet's host star will influence our ability to detect and interpret spectral features, including biosignatures. We present a complete suit of stellar models and a grid of model atmospheres for Earth-like planets at equivalent stages of geological evolution in their HZ for stellar effective temperature from Teff = 2300K to 7000K, sampling the entire FGKM stellar type range. Since M dwarfs are simultaneously the most numerous in the universe, the most active, and the most likely stars to host terrestrial exoplanets, we focus in particular on the range of UV emission possible in each sub M spectral class. The UV emission from a planet's host star dominates the photochemistry and thus the resultant observable spectral features of the planet. Using the latest UV spectra obtained by HST and IUE we model the effect of stellar activity on Earth-like planets. We also model the amount of UV flux reaching the surface for Earth-like planets at various geological epochs ranging from a pre-biotic world through the rise of oxygen and for Earth-like planets orbiting FGKM stars at equivalent stages of evolution. When modeling the remotely detectable spectra of these planets we focus on the primary detectable atmospheric features that indicate habitability on Earth, namely: H2O, CO2, O3, CH4, N2O and CH3Cl. We model the emergent as well as transit spectra of Earth-like planets orbiting our grid of FGKM stars in the VIS/NIR (0.4 - 4 μm) and the IR (5 - 20 μm) range as input for future missions like JWST and concepts like UVOIR/HDST.

Study on identifying deciduous forest by the method of feature space transformation

NASA Astrophysics Data System (ADS)

Zhang, Xuexia; Wu, Pengfei

2009-10-01

The thematic remotely sensed information extraction is always one of puzzling nuts which the remote sensing science faces, so many remote sensing scientists devotes diligently to this domain research. The methods of thematic information extraction include two kinds of the visual interpretation and the computer interpretation, the developing direction of which is intellectualization and comprehensive modularization. The paper tries to develop the intelligent extraction method of feature space transformation for the deciduous forest thematic information extraction in Changping district of Beijing city. The whole Chinese-Brazil resources satellite images received in 2005 are used to extract the deciduous forest coverage area by feature space transformation method and linear spectral decomposing method, and the result from remote sensing is similar to woodland resource census data by Chinese forestry bureau in 2004.

Spectroscopic analyses of Fe and water in clays: A Martian surface weathering study

NASA Technical Reports Server (NTRS)

Bishop, J. L.; Pieters, Carle M.; Edwards, J. O.; Coyne, L. M.; Chang, S.

1991-01-01

Martian surface morphology suggests the presence of liquid H2O on Mars in the past. Reflectance spectra of the Martian surface include features which correspond to the crystal field transitions of iron, as well as features supporting the presence of ice and minerals containing structural OH and surface water. Researchers initiated further spectroscopic studies of surface iron and water and structural OH in clays in order to determine what remotely obtained spectra can indicate about the presence of clays on Mars based on a clearer understanding of the factors influencing the spectral features. Current technology allows researchers to better correlate the low frequency fundamental stretching and bending vibrations of O-H bonds with the diagnostic near infrared overtone and combination bands used in mineral characterization and identification.

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.

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 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

Hyperspectral Feature Detection Onboard the Earth Observing One Spacecraft using Superpixel Segmentation and Endmember Extraction

NASA Technical Reports Server (NTRS)

Thompson, David R.; Bornstein, Benjamin; Bue, Brian D.; Tran, Daniel Q.; Chien, Steve A.; Castano, Rebecca

2012-01-01

We present a demonstration of onboard hyperspectral image processing with the potential to reduce mission downlink requirements. The system detects spectral endmembers and then uses them to map units of surface material. This summarizes the content of the scene, reveals spectral anomalies warranting fast response, and reduces data volume by two orders of magnitude. We have integrated this system into the Autonomous Science craft Experiment for operational use onboard the Earth Observing One (EO-1) Spacecraft. The system does not require prior knowledge about spectra of interest. We report on a series of trial overflights in which identical spacecraft commands are effective for autonomous spectral discovery and mapping for varied target features, scenes and imaging conditions.

A Developed Spectral Identification Tree for Mineral Mapping using Hyperspectral Data

NASA Astrophysics Data System (ADS)

Gan, Fuping; Wang, Runsheng; Yan, Bokun; Shang, Kun

2016-04-01

The relationship between the spectral features and the composition of minerals are the basis of mineral identification using hyperspectral data. The reflectance spectrum of minerals results from the systematic combination of several modes of interaction between electromagnetic energy and mineral particles in the form of reflection and absorption. Minerals tend to have absorbing features at specific wavelengths with a characteristic shape, which can be used as diagnostic indicators for identification. The spectral identification tree (SIT) method for mineral identification is developed in our research to map minerals accurately and applied in some typical mineral deposits in China. The SIT method is based on the diagnostic absorption features of minerals through comparing and statistically analyzing characteristic spectral data of minerals. We establish several levels of identification rules for the type, group and species of minerals using IF-THEN rule according to the spectral identification criteria so that the developed SIT can be further used to map minerals at different levels of detail from mineral type to mineral species. Identifiable minerals can be grouped into six types: Fe2+-bearing, Fe3+-bearing, Mn2+-bearing, Al-OH-bearing, Mg-OH-bearing and carbonate minerals. Each type can be further divided into several mineral groups. Each group contains several mineral species or specific minerals. A mineral spectral series, therefore, can be constructed as "type-group-species-specific mineral (mineral variety)" for mineral spectral identification. It is noted that the mineral classification is based mainly on spectral reflectance characteristics of minerals which may not be consistent with the classification in mineralogy. We applied the developed SIT method to the datasets acquired at the Eastern Tianshan Mountains of Xinjiang (HyMap data) and the Qulong district of Xizang (Hyperion data). In Xinjiang, the two major classes of Al-OH and Mg-OH minerals were mapped firstly. Then montmorillonite, kaolinite and muscovite were identified in the area of the Al-OH bearing minerals, and chlorite and epidote were identified in the area of the Mg-OH bearing minerals. Muscovite of rich Al and poor Al were further identified in the area of muscovite. In Xizang, Al-rich and Al-poor muscovite, kaolinite, chlorite and malachite were identified using SIT method. In all, the developed SIT method can further reduce the effect of other materials and focus on targeted minerals. In particular, the discrimination accuracy will be improved when the most diagnostic absorption spectral features are used in the developed SIT method.

Detecting molecular features of spectra mainly associated with structural and non-structural carbohydrates in co-products from bioEthanol production using DRIFT with uni- and multivariate molecular spectral analyses.

PubMed

Yu, Peiqiang; Damiran, Daalkhaijav; Azarfar, Arash; Niu, Zhiyuan

2011-01-01

The objective of this study was to use DRIFT spectroscopy with uni- and multivariate molecular spectral analyses as a novel approach to detect molecular features of spectra mainly associated with carbohydrate in the co-products (wheat DDGS, corn DDGS, blend DDGS) from bioethanol processing in comparison with original feedstock (wheat (Triticum), corn (Zea mays)). The carbohydrates related molecular spectral bands included: A_Cell (structural carbohydrates, peaks area region and baseline: ca. 1485-1188 cm(-1)), A_1240 (structural carbohydrates, peak area centered at ca. 1240 cm(-1) with region and baseline: ca. 1292-1198 cm(-1)), A_CHO (total carbohydrates, peaks region and baseline: ca. 1187-950 cm(-1)), A_928 (non-structural carbohydrates, peak area centered at ca. 928 cm(-1) with region and baseline: ca. 952-910 cm(-1)), A_860 (non-structural carbohydrates, peak area centered at ca. 860 cm(-1) with region and baseline: ca. 880-827 cm(-1)), H_1415 (structural carbohydrate, peak height centered at ca. 1415 cm(-1) with baseline: ca. 1485-1188 cm(-1)), H_1370 (structural carbohydrate, peak height at ca. 1370 cm(-1) with a baseline: ca. 1485-1188 cm(-1)). The study shows that the grains had lower spectral intensity (KM Unit) of the cellulosic compounds of A_1240 (8.5 vs. 36.6, P < 0.05), higher (P < 0.05) intensities of the non-structural carbohydrate of A_928 (17.3 vs. 2.0) and A_860 (20.7 vs. 7.6) than their co-products from bioethanol processing. There were no differences (P > 0.05) in the peak area intensities of A_Cell (structural CHO) at 1292-1198 cm(-1) and A_CHO (total CHO) at 1187-950 cm(-1) with average molecular infrared intensity KM unit of 226.8 and 508.1, respectively. There were no differences (P > 0.05) in the peak height intensities of H_1415 and H_1370 (structural CHOs) with average intensities 1.35 and 1.15, respectively. The multivariate molecular spectral analyses were able to discriminate and classify between the corn and corn DDGS molecular spectra, but not wheat and wheat DDGS. This study indicated that the bioethanol processing changes carbohydrate molecular structural profiles, compared with the original grains. However, the sensitivities of different types of carbohydrates and different grains (corn and wheat) to the processing differ. In general, the bioethanol processing increases the molecular spectral intensities for the structural carbohydrates and decreases the intensities for the non-structural carbohydrates. Further study is needed to quantify carbohydrate related molecular spectral features of the bioethanol co-products in relation to nutrient supply and availability of carbohydrates.

Study and simulation results for video landmark acquisition and tracking technology (Vilat-2)

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Tietz, J. C.; Thomas, H. M.; Gremban, K. D.; Hughes, C.; Chang, C. Y.

1983-01-01

The results of several investigations and hardware developments which supported new technology for Earth feature recognition and classification are described. Data analysis techniques and procedures were developed for processing the Feature Identification and Location Experiment (FILE) data. This experiment was flown in November 1981, on the second Shuttle flight and a second instrument, designed for aircraft flights, was flown over the United States in 1981. Ground tests were performed to provide the basis for designing a more advanced version (four spectral bands) of the FILE which would be capable of classifying clouds and snow (and possibly ice) as distinct features, in addition to the features classified in the Shuttle experiment (two spectral bands). The Shuttle instrument classifies water, bare land, vegetation, and clouds/snow/ice (grouped).

Groupwise shape analysis of the hippocampus using spectral matching

NASA Astrophysics Data System (ADS)

Shakeri, Mahsa; Lombaert, Hervé; Lippé, Sarah; Kadoury, Samuel

2014-03-01

The hippocampus is a prominent subcortical feature of interest in many neuroscience studies. Its subtle morphological changes often predicate illnesses, including Alzheimer's, schizophrenia or epilepsy. The precise location of structural differences requires a reliable correspondence between shapes across a population. In this paper, we propose an automated method for groupwise hippocampal shape analysis based on a spectral decomposition of a group of shapes to solve the correspondence problem between sets of meshes. The framework generates diffeomorphic correspondence maps across a population, which enables us to create a mean shape. Morphological changes are then located between two groups of subjects. The performance of the proposed method was evaluated on a dataset of 42 hippocampus shapes and compared with a state-of-the-art structural shape analysis approach, using spherical harmonics. Difference maps between mean shapes of two test groups demonstrates that the two approaches showed results with insignificant differences, while Gaussian curvature measures calculated between matched vertices showed a better fit and reduced variability with spectral matching.

Observations of southern emission-line stars

NASA Technical Reports Server (NTRS)

Henize, K. G.

1976-01-01

A catalog of 1929 stars showing H-alpha emission on photographic plates is presented which covers the entire southern sky south of declination -25 deg to a red limiting magnitude of about 11.0. The catalog provides previous designations of known emission-line stars equatorial (1900) and galactic coordinates, visual and photographic magnitudes, H-alpha emission parameters, spectral types, and notes on unusual spectral features. The objects listed include 16 M stars, 25 S stars, 37 carbon stars, 20 symbiotic stars, 40 confirmed or suspected T Tauri stars, 16 novae, 14 planetary nebulae, 11 P Cygni stars, 9 Bep stars, 87 confirmed or suspected Wolf-Rayet stars, and 26 'peculiar' stars. Two new T associations are discovered, one in Lupus and one in Chamaeleon. Objects with variations in continuum or H-alpha intensity are noted, and the distribution by spectral type is analyzed. It is found that the sky distribution of these emission-line stars shows significant concentrations in the region of the small Sagittarius cloud and in the Carina region.

Cloud classification in polar regions using AVHRR textural and spectral signatures

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Weger, R. C.; Christopher, S. A.; Kuo, K. S.; Carsey, F. D.

1990-01-01

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

The Copernicus ultraviolet spectral atlas of Vega

NASA Technical Reports Server (NTRS)

Rogerson, John B., Jr.

1989-01-01

A near-ultraviolet spectral atlas for the A0 V star Alpha Lyr (Vega) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 2000 to 3187 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs with a normalized continuum, and an identification table for the absorption features has been prepared.

Indirect searches of dark matter via polynomial spectral features

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

Garcia-Cely, Camilo; Heeck, Julian

2016-08-11

We derive the spectra arising from non-relativistic dark matter annihilations or decays into intermediary particles with arbitrary spin, which subsequently produce neutrinos or photons via two-body decays. Our approach is model independent and predicts spectral features restricted to a kinematic box. The overall shape within that box is a polynomial determined by the polarization of the decaying particle. We illustrate our findings with two examples. First, with the neutrino spectra arising from dark matter annihilations into the massive Standard Model gauge bosons. Second, with the gamma-ray and neutrino spectra generated by dark matter annihilations into hypothetical massive spin-2 particles. Ourmore » results are in particular applicable to the 750 GeV diphoton excess observed at the LHC if interpreted as a spin-0 or spin-2 particle coupled to dark matter. We also derive limits on the dark matter annihilation cross section into this resonance from the non-observation of the associated gamma-ray spectral features by the H.E.S.S. telescope.« less

Spectrally queued feature selection for robotic visual odometery

NASA Astrophysics Data System (ADS)

Pirozzo, David M.; Frederick, Philip A.; Hunt, Shawn; Theisen, Bernard; Del Rose, Mike

2011-01-01

Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.

A comparison of three feature selection methods for object-based classification of sub-decimeter resolution UltraCam-L imagery

USDA-ARS?s Scientific Manuscript database

The availability of numerous spectral, spatial, and contextual features with object-based image analysis (OBIA) renders the selection of optimal features a time consuming and subjective process. While several feature election methods have been used in conjunction with OBIA, a robust comparison of th...

Discriminating Induced-Microearthquakes Using New Seismic Features

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

High-resolution 3-μm spectra of Jupiter: Latitudinal spectral variations influenced by molecules, clouds, and haze

NASA Astrophysics Data System (ADS)

Kim, Sang J.; Geballe, T. R.; Kim, J. H.; Jung, A.; Seo, H. J.; Minh, Y. C.

2010-08-01

We present latitudinally-resolved high-resolution ( R = 37,000) pole-to-pole spectra of Jupiter in various narrow longitudinal ranges, in spectral intervals covering roughly half of the spectral range 2.86-3.53 μm. We have analyzed the data with the aid of synthetic spectra generated from a model jovian atmosphere that included lines of CH 4, CH 3D, NH 3, C 2H 2, C 2H 6, PH 3, and HCN, as well as clouds and haze. Numerous spectral features of many of these molecular species are present and are individually identified for the first time, as are many lines of H3+ and a few unidentified spectral features. In both polar regions the 2.86-3.10-μm continuum is more than 10 times weaker than in spectra at lower latitudes, implying that in this wavelength range the single-scattering albedos of polar haze particles are very low. In contrast, the 3.24-3.53 μm the weak polar and equatorial continua are of comparable intensity. We derive vertical distributions of NH 3, C 2H 2 and C 2H 6, and find that the mixing ratios of NH 3 and C 2H 6 show little variation between equatorial and polar regions. However, the mixing ratios of C 2H 2 in the northern and southern polar regions are ˜6 and ˜3 times, respectively, less than those in the equatorial regions. The derived mixing ratio curves of C 2H 2 and C 2H 6 extend up to the 10 -6 bar level, a significantly higher altitude than most previous results in the literature. Further ground-based observations covering other longitudes are needed to test if these mixing ratios are representative values for the equatorial and polar regions.

Complex Organic Materials on Planetary Satellites and Other Small Bodies of the Solar System

NASA Technical Reports Server (NTRS)

Cruikshank, Dale P.

2006-01-01

The search for organic materials on small bodies of the Solar System is conducted spectroscopically from Earth-based telescopes and from spacecraft. Although the carbonaceous meteorites carry a significant inventory of complex organic solids, the sources of these meteorites have not been identified. Infrared spectra of a sample of the suspected sources, the C- and D-class asteroids, including new data from the Spitzer Space Telescope, show signatures of silicates, but none diagnostic of organic compounds. In the absence of discrete spectral features, the low albedos and colors in the visible and near-IR spectral regions are the principal links between the organic-bearing meteorites and the asteroids. While Pluto and a few trans-neptunian objects show spectral signatures of frozen CH4. Solid CH3OH has been identified on two Centaur objects in the outer Solar System. In some cases the red colors of those objects suggest the presence of tholins. The VIMS instrument aboard the Cassini spacecraft in orbit around Saturn has detected near-IR spectral features on at least three of Saturn's satellites that are indicative or suggestive of organic molecules. One entire hemisphere of the satellite Iapetus is covered with low-albedo material that shows a spectral signature of aromatic hydrocarbons (3.3 microns) and the -CH2 stretching mode bands of an aliphatic component. Organics absorbing at 3.44 microns are suspected in the region of the south pole of Enceladus, and also on the surface of Phoebe. Organic material may originate on icy bodies in the current epoch by various processes of energy deposition into native material, or they may fall to the surface from an external (probably cometary) source. Some organic material may be pre-solar, having originated in the interstellar medium before the formation of the Solar System. Using the techniques of remote sensing, its detection and analysis are slow and difficult.

Intercomparison of Carbonate Deposits on Mars: VNIR Spectral Character and Geologic Context

NASA Astrophysics Data System (ADS)

Wiseman, S.; Mustard, J. F.; Ehlmann, B. L.

2012-12-01

Carbonate-bearing deposits were identified on Mars at multiple locations using CRISM VNIR spectral data [1,2,3,4,5]. Carbonates exhibit distinctive C-O related absorption features near 2300, 2500, 3400 and 3900nm that can be used to identify specific carbonate phases (e.g., Mg-carbonates have band minima at 2300/2500nm and Fe-carbonates have minima at 2330/2530nm [6]). The features at 2300 and 2500nm are the focus of most CRISM analyses because this part of the spectral range is well calibrated, lacks strong contributions from thermal emission, and is not impacted by strong water-related absorptions near 3000nm (e.g., in Fe/Mg phyllosilicates). However, multiple other phases also exhibit features near 2300 and 2500nm.For carbonates, the depth of the 2500nm feature is stronger than at 2300nm as opposed to most Fe/Mg phyllosilicates. Mixing of the carbonate with other phases in CRISM pixels impacts the band centers and strengths of the 2300 and 2500nm features and therefore complicates identification of the carbonate phase(s) responsible for observed CRISM spectral features. In this study we analyze CRISM data fully corrected for the atmosphere using DISORT radiative transfer modeling [7,8] to evaluate CRISM spectra of multiple carbonate-bearing deposits. Rigorous intercomparison of CRISM spectra extracted from different images is affected by variable aerosol, CO2 and water vapor features left by the standard volcano scan empirical atmospheric correction [9]. While residual gas absorptions are commonly suppressed by ratioing, the appearance of spectral features in ratio spectra is impacted by spectral features in the dominator spectrum compromising detailed assessments of ratio spectra derived from different images. Atmospheric correction is particularly important for interpreting carbonate deposits because the 2500nm carbonate feature overlaps with atmospheric water vapor absorptions. In Nili Fossae, carbonates occur in association with olivine, smectite, serpentine [1,10], and possibly talc [11].These carbonates are hypothesized to have formed via alteration of olivine and/or serpentine under surface or low temperature hydrothermal conditions [1,11,12] Laboratory spectra of Mg carbonates (magnesite/hydromagnesite) are the closest matches to the Nili Fossae carbonates [1]. CRISM spectra of carbonates in and around Huygens basin are interpreted to be Fe and/or Ca carbonates [3], similar to carbonate spectra described by [2]. However, the CRISM carbonate-bearing spectra are mixed with Fe/Mg phyllosilicates [1,2,3], making a one to one comparison among Martian and laboratory carbonate spectra challenging. [1] Ehlmann et al. (2008), Sci., 322, 1828-1831, [2] Michalski and. Niles (2010), Nat. Geo., 3, 751-55, [3] Wray et al. (2011), LPSC, #2635, [4] Bishop et al. (2012), LPSC, #2330, [5] Carter and Poulet (2012), Icarus, [6] Gaffey (1987), JGR, 92, 1429-1440, [7] Stamnes et al. (1999), Appl. Opt., 27, 2502-2509, [8] Wolff et al. (2009), JGR, 11, [9] Wiseman et al., 2010, LPSC , #2461, [10] Ehlmann et al. (2010), GRL, 37, [11] Brown et al. (2010), EPSL, 297, 174-182. [12] Ehlmann et al. (2009), JGR, 114.

Using Whispering-Gallery-Mode Resonators for Refractometry

NASA Technical Reports Server (NTRS)

Matsko, Andrey; Savchenkov, Anatoliy; Strekalov, Dmitry; Iltchenko, Vladimir; Maleki, Lute

2010-01-01

A method of determining the refractive and absorptive properties of optically transparent materials involves a combination of theoretical and experimental analysis of electromagnetic responses of whispering-gallery-mode (WGM) resonator disks made of those materials. The method was conceived especially for use in studying transparent photorefractive materials, for which purpose this method affords unprecedented levels of sensitivity and accuracy. The method is expected to be particularly useful for measuring temporally varying refractive and absorptive properties of photorefractive materials at infrared wavelengths. Still more particularly, the method is expected to be useful for measuring drifts in these properties that are so slow that, heretofore, the properties were assumed to be constant. The basic idea of the method is to attempt to infer values of the photorefractive properties of a material by seeking to match (1) theoretical predictions of the spectral responses (or selected features thereof) of a WGM of known dimensions made of the material with (2) the actual spectral responses (or selected features thereof). Spectral features that are useful for this purpose include resonance frequencies, free spectral ranges (differences between resonance frequencies of adjacently numbered modes), and resonance quality factors (Q values). The method has been demonstrated in several experiments, one of which was performed on a WGM resonator made from a disk of LiNbO3 doped with 5 percent of MgO. The free spectral range of the resonator was approximately equal to 3.42 GHz at wavelengths in the vicinity of 780 nm, the smallest full width at half maximum of a mode was approximately equal to 50 MHz, and the thickness of the resonator in the area of mode localization was 30 microns. In the experiment, laser power of 9 mW was coupled into the resonator with an efficiency of 75 percent, and the laser was scanned over a frequency band 9 GHz wide at a nominal wavelength of approximately equal to 780 nm. Resonance frequencies were measured as functions of time during several hours of exposure to the laser light. The results of these measurements, plotted in the figure, show a pronounced collective frequency drift of the resonator modes. The size of the drift has been estimated to correspond to a change of 8.5 x 10(exp -5) in the effective ordinary index of refraction of the resonator material.

Use of field reflectance data for crop mapping using airborne hyperspectral image

NASA Astrophysics Data System (ADS)

Nidamanuri, Rama Rao; Zbell, Bernd

2011-09-01

Recent developments in hyperspectral remote sensing technologies enable acquisition of image with high spectral resolution, which is typical to the laboratory or in situ reflectance measurements. There has been an increasing interest in the utilization of in situ reference reflectance spectra for rapid and repeated mapping of various surface features. Here we examined the prospect of classifying airborne hyperspectral image using field reflectance spectra as the training data for crop mapping. Canopy level field reflectance measurements of some important agricultural crops, i.e. alfalfa, winter barley, winter rape, winter rye, and winter wheat collected during four consecutive growing seasons are used for the classification of a HyMAP image acquired for a separate location by (1) mixture tuned matched filtering (MTMF), (2) spectral feature fitting (SFF), and (3) spectral angle mapper (SAM) methods. In order to answer a general research question "what is the prospect of using independent reference reflectance spectra for image classification", while focussing on the crop classification, the results indicate distinct aspects. On the one hand, field reflectance spectra of winter rape and alfalfa demonstrate excellent crop discrimination and spectral matching with the image across the growing seasons. On the other hand, significant spectral confusion detected among the winter barley, winter rye, and winter wheat rule out the possibility of existence of a meaningful spectral matching between field reflectance spectra and image. While supporting the current notion of "non-existence of characteristic reflectance spectral signatures for vegetation", results indicate that there exist some crops whose spectral signatures are similar to characteristic spectral signatures with possibility of using them in image classification.

Processing of spectral and amplitude envelope of animal vocalizations in the human auditory cortex.

PubMed

Altmann, Christian F; Gomes de Oliveira Júnior, Cícero; Heinemann, Linda; Kaiser, Jochen

2010-08-01

In daily life, we usually identify sounds effortlessly and efficiently. Two properties are particularly salient and of importance for sound identification: the sound's overall spectral envelope and its temporal amplitude envelope. In this study, we aimed at investigating the representation of these two features in the human auditory cortex by using a functional magnetic resonance imaging adaptation paradigm. We presented pairs of sound stimuli derived from animal vocalizations that preserved the time-averaged frequency spectrum of the animal vocalizations and the amplitude envelope. We presented the pairs in four different conditions: (a) pairs with the same amplitude envelope and mean spectral envelope, (b) same amplitude envelope, but different mean spectral envelope, (c) different amplitude envelope, but same mean spectral envelope and (d) both different amplitude envelope and mean spectral envelope. We found fMRI adaptation effects for both the mean spectral envelope and the amplitude envelope of animal vocalizations in overlapping cortical areas in the bilateral superior temporal gyrus posterior to Heschl's gyrus. Areas sensitive to the amplitude envelope extended further anteriorly along the lateral superior temporal gyrus in the left hemisphere, while areas sensitive to the spectral envelope extended further anteriorly along the right lateral superior temporal gyrus. Posterior tonotopic areas within the left superior temporal lobe displayed sensitivity for the mean spectrum. Our findings suggest involvement of primary auditory areas in the representation of spectral cues and encoding of general spectro-temporal features of natural sounds in non-primary posterior and lateral superior temporal cortex. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Characterization of Cryptosporidium parvum by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

PubMed Central

Magnuson, Matthew L.; Owens, James H.; Kelty, Catherine A.

2000-01-01

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) was used to investigate whole and freeze-thawed Cryptosporidium parvum oocysts. Whole oocysts revealed some mass spectral features. Reproducible patterns of spectral markers and increased sensitivity were obtained after the oocysts were lysed with a freeze-thaw procedure. Spectral-marker patterns for C. parvum were distinguishable from those obtained for Cryptosporidium muris. One spectral marker appears specific for the genus, while others appear specific at the species level. Three different C. parvum lots were investigated, and similar spectral markers were observed in each. Disinfection of the oocysts reduced and/or eliminated the patterns of spectral markers. PMID:11055915

Demonstration of spectral correlation control in a source of polarization-entangled photon pairs at telecom wavelength.

PubMed

Lutz, Thomas; Kolenderski, Piotr; Jennewein, Thomas

2014-03-15

Spectrally correlated photon pairs can be used to improve the performance of long-range fiber-based quantum communication protocols. We present a source based on spontaneous parametric downconversion, which allows one to control spectral correlations within the entangled photon pair without spectral filtering by changing the pump-pulse duration or the characteristics of the coupled spatial modes. The spectral correlations and polarization entanglement are characterized. We find that the generated photon pairs can feature both positive spectral correlations, decorrelation, or negative correlations at the same time as polarization entanglement with a high fidelity of 0.97 (no background subtraction) with the expected Bell state.

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.

Multipurpose Hyperspectral Imaging System

NASA Technical Reports Server (NTRS)

Mao, Chengye; Smith, David; Lanoue, Mark A.; Poole, Gavin H.; Heitschmidt, Jerry; Martinez, Luis; Windham, William A.; Lawrence, Kurt C.; Park, Bosoon

2005-01-01

A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral imaging with or without relative movement of the imaging system, and it can be used to scan a target of any size as long as the target can be imaged at the focal plane; for example, automated inspection of food items and identification of single-celled organisms. The spectral resolution of this system is greater than that of prior terrestrial multispectral imaging systems. Moreover, unlike prior high-spectral resolution airborne and spaceborne hyperspectral imaging systems, this system does not rely on relative movement of the target and the imaging system to sweep an imaging line across a scene. This compact system (see figure) consists of a front objective mounted at a translation stage with a motorized actuator, and a line-slit imaging spectrograph mounted within a rotary assembly with a rear adaptor to a charged-coupled-device (CCD) camera. Push-broom scanning is carried out by the motorized actuator which can be controlled either manually by an operator or automatically by a computer to drive the line-slit across an image at a focal plane of the front objective. To reduce the cost, the system has been designed to integrate as many as possible off-the-shelf components including the CCD camera and spectrograph. The system has achieved high spectral and spatial resolutions by using a high-quality CCD camera, spectrograph, and front objective lens. Fixtures for attachment of the system to a microscope (U.S. Patent 6,495,818 B1) make it possible to acquire multispectral images of single cells and other microscopic objects.

A TALE OF THREE MYSTERIOUS SPECTRAL FEATURES IN CARBON-RICH EVOLVED STARS: THE 21 μm, 30 μm, AND “UNIDENTIFIED INFRARED” EMISSION FEATURES

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

Mishra, Ajay; Li, Aigen; Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn

2015-03-20

The mysterious “21 μm” emission feature seen almost exclusively in the short-lived protoplanetary nebula (PPN) phase of stellar evolution remains unidentified since its discovery two decades ago. This feature is always accompanied by the equally mysterious, unidentified “30 μm” feature and the so-called “unidentified infrared” (UIR) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μm which are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. The 30 μm feature is commonly observed in all stages of stellar evolution from the asymptotic giant branch through PPN to the planetary nebula phase. We explore the interrelations among the mysterious 21, 30 μm,more » and UIR features of the 21 μm sources. We derive the fluxes emitted in the observed UIR, 21, and 30 μm features from published Infrared Space Observatory or Spitzer/IRS spectra. We find that none of these spectral features correlate with each other. This argues against a common carrier (e.g., thiourea) for both the 21 μm feature and the 30 μm feature. This also does not support large PAH clusters as a possible carrier for the 21 μm feature.« less

Simulation of the hyperspectral data from multispectral data using Python programming language

NASA Astrophysics Data System (ADS)

Tiwari, Varun; Kumar, Vinay; Pandey, Kamal; Ranade, Rigved; Agarwal, Shefali

2016-04-01

Multispectral remote sensing (MRS) sensors have proved their potential in acquiring and retrieving information of Land Use Land (LULC) Cover features in the past few decades. These MRS sensor generally acquire data within limited broad spectral bands i.e. ranging from 3 to 10 number of bands. The limited number of bands and broad spectral bandwidth in MRS sensors becomes a limitation in detailed LULC studies as it is not capable of distinguishing spectrally similar LULC features. On the counterpart, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of the earth surface. But presently the availability of HRS sensors is limited. This is because of the requirement of sensitive detectors and large storage capability, which makes the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MRS data for detailed LULC studies. Spectral reconstruction approach is one of the technique used for simulating hyperspectral data from available multispectral data. In the present study, spectral reconstruction approach is utilized for the simulation of hyperspectral data using EO-1 ALI multispectral data. The technique is implemented using python programming language which is open source in nature and possess support for advanced imaging processing libraries and utilities. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.