Radio-nuclide mixture identification using medium energy resolution detectors

DOEpatents

Nelson, Karl Einar

2013-09-17

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

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh-Dokhtar Volcanic Belt, Iran

NASA Astrophysics Data System (ADS)

Pour, Amin Beiranvand; Hashim, Mazlan

2012-02-01

This study investigates the application of spectral image processing methods to ASTER data for mapping hydrothermal alteration zones associated with porphyry copper mineralization and related host rock. The study area is located in the southeastern segment of the Urumieh-Dokhtar Volcanic Belt of Iran. This area has been selected because it is a potential zone for exploration of new porphyry copper deposits. Spectral transform approaches, namely principal component analysis, band ratio and minimum noise fraction were used for mapping hydrothermally altered rocks and lithological units at regional scale. Spectral mapping methods, including spectral angle mapper, linear spectral unmixing, matched filtering and mixture tuned matched filtering were applied to differentiate hydrothermal alteration zones associated with porphyry copper mineralization such as phyllic, argillic and propylitic mineral assemblages.Spectral transform methods enhanced hydrothermally altered rocks associated with the known porphyry copper deposits and new identified prospects using shortwave infrared (SWIR) bands of ASTER. These methods showed the discrimination of quartz rich igneous rocks from the magmatic background and the boundary between igneous and sedimentary rocks using the thermal infrared (TIR) bands of ASTER at regional scale. Spectral mapping methods distinguished the sericitically- and argillically-altered rocks (the phyllic and argillic alteration zones) that surrounded by discontinuous to extensive zones of propylitized rocks (the propylitic alteration zone) using SWIR bands of ASTER at both regional and district scales. Linear spectral unmixing method can be best suited for distinguishing specific high economic-potential hydrothermal alteration zone (the phyllic zone) and mineral assemblages using SWIR bands of ASTER. Results have proven to be effective, and in accordance with the results of field surveying, spectral reflectance measurements and X-ray diffraction (XRD) analysis. In conclusion, the image processing methods used can provide cost-effective information to discover possible locations of porphyry copper and epithermal gold mineralization prior to detailed and costly ground investigations. The extraction of spectral information from ASTER data can produce comprehensive and accurate information for copper and gold resource investigations around the world, including those yet to be discovered.

Spectral identification of melon seeds variety based on k-nearest neighbor and Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Li, Cuiling; Jiang, Kai; Zhao, Xueguan; Fan, Pengfei; Wang, Xiu; Liu, Chuan

2017-10-01

Impurity of melon seeds variety will cause reductions of melon production and economic benefits of farmers, this research aimed to adopt spectral technology combined with chemometrics methods to identify melon seeds variety. Melon seeds whose varieties were "Yi Te Bai", "Yi Te Jin", "Jing Mi NO.7", "Jing Mi NO.11" and " Yi Li Sha Bai "were used as research samples. A simple spectral system was developed to collect reflective spectral data of melon seeds, including a light source unit, a spectral data acquisition unit and a data processing unit, the detection wavelength range of this system was 200-1100nm with spectral resolution of 0.14 7.7nm. The original reflective spectral data was pre-treated with de-trend (DT), multiple scattering correction (MSC), first derivative (FD), normalization (NOR) and Savitzky-Golay (SG) convolution smoothing methods. Principal Component Analysis (PCA) method was adopted to reduce the dimensions of reflective spectral data and extract principal components. K-nearest neighbour (KNN) and Fisher discriminant analysis (FDA) methods were used to develop discriminant models of melon seeds variety based on PCA. Spectral data pretreatments improved the discriminant effects of KNN and FDA, FDA generated better discriminant results than KNN, both KNN and FDA methods produced discriminant accuracies reaching to 90.0% for validation set. Research results showed that using spectral technology in combination with KNN and FDA modelling methods to identify melon seeds variety was feasible.

CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model.

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

Dennis, John; Edwards, Jim; Evans, Kate J

2012-01-01

The Community Atmosphere Model (CAM) version 5 includes a spectral element dynamical core option from NCAR's High-Order Method Modeling Environment. It is a continuous Galerkin spectral finite element method designed for fully unstructured quadrilateral meshes. The current configurations in CAM are based on the cubed-sphere grid. The main motivation for including a spectral element dynamical core is to improve the scalability of CAM by allowing quasi-uniform grids for the sphere that do not require polar filters. In addition, the approach provides other state-of-the-art capabilities such as improved conservation properties. Spectral elements are used for the horizontal discretization, while most othermore » aspects of the dynamical core are a hybrid of well tested techniques from CAM's finite volume and global spectral dynamical core options. Here we first give a overview of the spectral element dynamical core as used in CAM. We then give scalability and performance results from CAM running with three different dynamical core options within the Community Earth System Model, using a pre-industrial time-slice configuration. We focus on high resolution simulations of 1/4 degree, 1/8 degree, and T340 spectral truncation.« less

Spectrally-engineered solar thermal photovoltaic devices

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

Lenert, Andrej; Bierman, David; Chan, Walker

A solar thermal photovoltaic device, and method of forming same, includes a solar absorber and a spectrally selective emitter formed on either side of a thermally conductive substrate. The solar absorber is configured to absorb incident solar radiation. The solar absorber and the spectrally selective emitter are configured with an optimized emitter-to-absorber area ratio. The solar thermal photovoltaic device also includes a photovoltaic cell in thermal communication with the spectrally selective emitter. The spectrally selective emitter is configured to permit high emittance for energies above a bandgap of the photovoltaic cell and configured to permit low emittance for energies belowmore » the bandgap.« less

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

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

2018-02-01

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

Adaptive mesh strategies for the spectral element method

NASA Technical Reports Server (NTRS)

Mavriplis, Catherine

1992-01-01

An adaptive spectral method was developed for the efficient solution of time dependent partial differential equations. Adaptive mesh strategies that include resolution refinement and coarsening by three different methods are illustrated on solutions to the 1-D viscous Burger equation and the 2-D Navier-Stokes equations for driven flow in a cavity. Sharp gradients, singularities, and regions of poor resolution are resolved optimally as they develop in time using error estimators which indicate the choice of refinement to be used. The adaptive formulation presents significant increases in efficiency, flexibility, and general capabilities for high order spectral methods.

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

PubMed

Liu, Da; Li, Jianxun

2016-12-16

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

[The application of spectral geological profile in the alteration mapping].

PubMed

Li, Qing-Ting; Lin, Qi-Zhong; Zhang, Bing; Lu, Lin-Lin

2012-07-01

Geological section can help validating and understanding of the alteration information which is extracted from remote sensing images. In the paper, the concept of spectral geological profile was introduced based on the principle of geological section and the method of spectral information extraction. The spectral profile can realize the storage and vision of spectra along the geological profile, but the spectral geological spectral profile includes more information besides the information of spectral profile. The main object of spectral geological spectral profile is to obtain the distribution of alteration types and content of minerals along the profile which can be extracted from spectra measured by field spectrometer, especially for the spatial distribution and mode of alteration association. Technical method and work flow of alteration information extraction was studied for the spectral geological profile. The spectral geological profile was set up using the ground reflectance spectra and the alteration information was extracted from the remote sensing image with the help of typical spectra geological profile. At last the meaning and effect of the spectral geological profile was discussed.

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.

An Analysis of Periodic Components in BL Lac Object S5 0716 +714 with MUSIC Method

NASA Astrophysics Data System (ADS)

Tang, J.

2012-01-01

Multiple signal classification (MUSIC) algorithms are introduced to the estimation of the period of variation of BL Lac objects.The principle of MUSIC spectral analysis method and theoretical analysis of the resolution of frequency spectrum using analog signals are included. From a lot of literatures, we have collected a lot of effective observation data of BL Lac object S5 0716 + 714 in V, R, I bands from 1994 to 2008. The light variation periods of S5 0716 +714 are obtained by means of the MUSIC spectral analysis method and periodogram spectral analysis method. There exist two major periods: (3.33±0.08) years and (1.24±0.01) years for all bands. The estimation of the period of variation of the algorithm based on the MUSIC spectral analysis method is compared with that of the algorithm based on the periodogram spectral analysis method. It is a super-resolution algorithm with small data length, and could be used to detect the period of variation of weak signals.

Identification of spectral regions for the quantification of red wine tannins with fourier transform mid-infrared spectroscopy.

PubMed

Jensen, Jacob S; Egebo, Max; Meyer, Anne S

2008-05-28

Accomplishment of fast tannin measurements is receiving increased interest as tannins are important for the mouthfeel and color properties of red wines. Fourier transform mid-infrared spectroscopy allows fast measurement of different wine components, but quantification of tannins is difficult due to interferences from spectral responses of other wine components. Four different variable selection tools were investigated for the identification of the most important spectral regions which would allow quantification of tannins from the spectra using partial least-squares regression. The study included the development of a new variable selection tool, iterative backward elimination of changeable size intervals PLS. The spectral regions identified by the different variable selection methods were not identical, but all included two regions (1485-1425 and 1060-995 cm(-1)), which therefore were concluded to be particularly important for tannin quantification. The spectral regions identified from the variable selection methods were used to develop calibration models. All four variable selection methods identified regions that allowed an improved quantitative prediction of tannins (RMSEP = 69-79 mg of CE/L; r = 0.93-0.94) as compared to a calibration model developed using all variables (RMSEP = 115 mg of CE/L; r = 0.87). Only minor differences in the performance of the variable selection methods were observed.

Extracting attosecond delays from spectrally overlapping interferograms

NASA Astrophysics Data System (ADS)

Jordan, Inga; Wörner, Hans Jakob

2018-02-01

Attosecond interferometry is becoming an increasingly popular technique for measuring the dynamics of photoionization in real time. Whereas early measurements focused on atomic systems with very simple photoelectron spectra, the technique is now being applied to more complex systems including isolated molecules and solids. The increase in complexity translates into an augmented spectral congestion, unavoidably resulting in spectral overlap in attosecond interferograms. Here, we discuss currently used methods for phase retrieval and introduce two new approaches for determining attosecond photoemission delays from spectrally overlapping photoelectron spectra. We show that the previously used technique, consisting in the spectral integration of the areas of interest, does in general not provide reliable results. Our methods resolve this problem, thereby opening the technique of attosecond interferometry to complex systems and fully exploiting its specific advantages in terms of spectral resolution compared to attosecond streaking.

Spectral properties of thermal fluctuations on simple liquid surfaces below shot-noise levels.

PubMed

Aoki, Kenichiro; Mitsui, Takahisa

2012-07-01

We study the spectral properties of thermal fluctuations on simple liquid surfaces, sometimes called ripplons. Analytical properties of the spectral function are investigated and are shown to be composed of regions with simple analytic behavior with respect to the frequency or the wave number. The derived expressions are compared to spectral measurements performed orders of magnitude below shot-noise levels, which is achieved using a novel noise reduction method. The agreement between the theory of thermal surface fluctuations and the experiment is found to be excellent, elucidating the spectral properties of the surface fluctuations. The measurement method requires relatively only a small sample both spatially (few μm) and temporally (~20 s). The method also requires relatively weak light power (~0.5 mW) so that it has a broad range of applicability, including local measurements, investigations of time-dependent phenomena, and noninvasive measurements.

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.

New format presentation for infrared spectral emittance data. Infrared spectrometry studies, phase 5

NASA Technical Reports Server (NTRS)

Lyon, R. J. P.; Green, A. A.

1972-01-01

Methods for infrared radiance measurements from geological materials were studied for airborne use over terrains with minimal vegetation. The tasks of the investigation were: (1) calculation of emittance ratios, (2) comparison of IR spectral emittance data with K-band scatterometer data over Pisgah Crater, and (3) standard infrared spectral file. Published papers reporting the research are included.

Detection of illicit substances in fingerprints by infrared spectral imaging.

PubMed

Ng, Ping Hei Ronnie; Walker, Sarah; Tahtouh, Mark; Reedy, Brian

2009-08-01

FTIR and Raman spectral imaging can be used to simultaneously image a latent fingerprint and detect exogenous substances deposited within it. These substances might include drugs of abuse or traces of explosives or gunshot residue. In this work, spectral searching algorithms were tested for their efficacy in finding targeted substances deposited within fingerprints. "Reverse" library searching, where a large number of possibly poor-quality spectra from a spectral image are searched against a small number of high-quality reference spectra, poses problems for common search algorithms as they are usually implemented. Out of a range of algorithms which included conventional Euclidean distance searching, the spectral angle mapper (SAM) and correlation algorithms gave the best results when used with second-derivative image and reference spectra. All methods tested gave poorer performances with first derivative and undifferentiated spectra. In a search against a caffeine reference, the SAM and correlation methods were able to correctly rank a set of 40 confirmed but poor-quality caffeine spectra at the top of a dataset which also contained 4,096 spectra from an image of an uncontaminated latent fingerprint. These methods also successfully and individually detected aspirin, diazepam and caffeine that had been deposited together in another fingerprint, and they did not indicate any of these substances as a match in a search for another substance which was known not to be present. The SAM was used to successfully locate explosive components in fingerprints deposited on silicon windows. The potential of other spectral searching algorithms used in the field of remote sensing is considered, and the applicability of the methods tested in this work to other modes of spectral imaging is discussed.

Laser-induced plasma characterization through self-absorption quantification

NASA Astrophysics Data System (ADS)

Hou, JiaJia; Zhang, Lei; Zhao, Yang; Yan, Xingyu; Ma, Weiguang; Dong, Lei; Yin, Wangbao; Xiao, Liantuan; Jia, Suotang

2018-07-01

A self-absorption quantification method is proposed to quantify the self-absorption degree of spectral lines, in which plasma characteristics including electron temperature, elemental concentration ratio, and absolute species number density can be deduced directly. Since there is no spectral intensity involved in the calculation, the analysis results are independent of the self-absorption effects and the additional spectral efficiency calibration is not required. In order to evaluate the practicality, the limitation for application and the precision of this method are also discussed. Experimental results of aluminum-lithium alloy prove that the proposed method is qualified to realize semi-quantitative measurements and fast plasma characteristics diagnostics.

A simple method of measuring the effective SRS coefficient in single-mode optical fibres and the range of its applicability

NASA Astrophysics Data System (ADS)

Shikhaliev, I. I.; Gainov, V. V.; Dorozhkin, A. N.; Nanii, O. E.; Konyshev, V. A.; Treshchikov, V. N.

2017-11-01

This paper describes techniques for measuring the SRS coefficient in a wide spectral range, including the region of small Stokes shifts. A simple, approximate method is proposed for evaluating the SRS coefficient near a gain peak. Spectral dependences of the SRS coefficient are presented for various telecom fibres.

Validation of Spectral Unmixing Results from Informed Non-Negative Matrix Factorization (INMF) of Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Wright, L.; Coddington, O.; Pilewskie, P.

2017-12-01

Hyperspectral instruments are a growing class of Earth observing sensors designed to improve remote sensing capabilities beyond discrete multi-band sensors by providing tens to hundreds of continuous spectral channels. Improved spectral resolution, range and radiometric accuracy allow the collection of large amounts of spectral data, facilitating thorough characterization of both atmospheric and surface properties. We describe the development of an Informed Non-Negative Matrix Factorization (INMF) spectral unmixing method to exploit this spectral information and separate atmospheric and surface signals based on their physical sources. INMF offers marked benefits over other commonly employed techniques including non-negativity, which avoids physically impossible results; and adaptability, which tailors the method to hyperspectral source separation. The INMF algorithm is adapted to separate contributions from physically distinct sources using constraints on spectral and spatial variability, and library spectra to improve the initial guess. Using this INMF algorithm we decompose hyperspectral imagery from the NASA Hyperspectral Imager for the Coastal Ocean (HICO), with a focus on separating surface and atmospheric signal contributions. HICO's coastal ocean focus provides a dataset with a wide range of atmospheric and surface conditions. These include atmospheres with varying aerosol optical thicknesses and cloud cover. HICO images also provide a range of surface conditions including deep ocean regions, with only minor contributions from the ocean surfaces; and more complex shallow coastal regions with contributions from the seafloor or suspended sediments. We provide extensive comparison of INMF decomposition results against independent measurements of physical properties. These include comparison against traditional model-based retrievals of water-leaving, aerosol, and molecular scattering radiances and other satellite products, such as aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS).

Authentication of Closely Related Fish and Derived Fish Products Using Tandem Mass Spectrometry and Spectral Library Matching.

PubMed

Nessen, Merel A; van der Zwaan, Dennis J; Grevers, Sander; Dalebout, Hans; Staats, Martijn; Kok, Esther; Palmblad, Magnus

2016-05-11

Proteomics methodology has seen increased application in food authentication, including tandem mass spectrometry of targeted species-specific peptides in raw, processed, or mixed food products. We have previously described an alternative principle that uses untargeted data acquisition and spectral library matching, essentially spectral counting, to compare and identify samples without the need for genomic sequence information in food species populations. Here, we present an interlaboratory comparison demonstrating how a method based on this principle performs in a realistic context. We also increasingly challenge the method by using data from different types of mass spectrometers, by trying to distinguish closely related and commercially important flatfish, and by analyzing heavily contaminated samples. The method was found to be robust in different laboratories, and 94-97% of the analyzed samples were correctly identified, including all processed and contaminated samples.

Selective suppression of high-order harmonics within phase-matched spectral regions.

PubMed

Lerner, Gavriel; Diskin, Tzvi; Neufeld, Ofer; Kfir, Ofer; Cohen, Oren

2017-04-01

Phase matching in high-harmonic generation leads to enhancement of multiple harmonics. It is sometimes desired to control the spectral structure within the phase-matched spectral region. We propose a scheme for selective suppression of high-order harmonics within the phase-matched spectral region while weakly influencing the other harmonics. The method is based on addition of phase-mismatched segments within a phase-matched medium. We demonstrate the method numerically in two examples. First, we show that one phase-mismatched segment can significantly suppress harmonic orders 9, 15, and 21. Second, we show that two phase-mismatched segments can efficiently suppress circularly polarized harmonics with one helicity over the other when driven by a bi-circular field. The new method may be useful for various applications, including the generation of highly helical bright attosecond pulses.

Approximate Solution Methods for Spectral Radiative Transfer in High Refractive Index Layers

NASA Technical Reports Server (NTRS)

Siegel, R.; Spuckler, C. M.

1994-01-01

Some ceramic materials for high temperature applications are partially transparent for radiative transfer. The refractive indices of these materials can be substantially greater than one which influences internal radiative emission and reflections. Heat transfer behavior of single and laminated layers has been obtained in the literature by numerical solutions of the radiative transfer equations coupled with heat conduction and heating at the boundaries by convection and radiation. Two-flux and diffusion methods are investigated here to obtain approximate solutions using a simpler formulation than required for exact numerical solutions. Isotropic scattering is included. The two-flux method for a single layer yields excellent results for gray and two band spectral calculations. The diffusion method yields a good approximation for spectral behavior in laminated multiple layers if the overall optical thickness is larger than about ten. A hybrid spectral model is developed using the two-flux method in the optically thin bands, and radiative diffusion in bands that are optically thick.

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.

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

NASA Technical Reports Server (NTRS)

1972-01-01

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

A time-spectral approach to numerical weather prediction

NASA Astrophysics Data System (ADS)

Scheffel, Jan; Lindvall, Kristoffer; Yik, Hiu Fai

2018-05-01

Finite difference methods are traditionally used for modelling the time domain in numerical weather prediction (NWP). Time-spectral solution is an attractive alternative for reasons of accuracy and efficiency and because time step limitations associated with causal CFL-like criteria, typical for explicit finite difference methods, are avoided. In this work, the Lorenz 1984 chaotic equations are solved using the time-spectral algorithm GWRM (Generalized Weighted Residual Method). Comparisons of accuracy and efficiency are carried out for both explicit and implicit time-stepping algorithms. It is found that the efficiency of the GWRM compares well with these methods, in particular at high accuracy. For perturbative scenarios, the GWRM was found to be as much as four times faster than the finite difference methods. A primary reason is that the GWRM time intervals typically are two orders of magnitude larger than those of the finite difference methods. The GWRM has the additional advantage to produce analytical solutions in the form of Chebyshev series expansions. The results are encouraging for pursuing further studies, including spatial dependence, of the relevance of time-spectral methods for NWP modelling.

[Study of near infrared spectral preprocessing and wavelength selection methods for endometrial cancer tissue].

PubMed

Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong

2010-04-01

Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.

Prediction Analysis for Measles Epidemics

NASA Astrophysics Data System (ADS)

Sumi, Ayako; Ohtomo, Norio; Tanaka, Yukio; Sawamura, Sadashi; Olsen, Lars Folke; Kobayashi, Nobumichi

2003-12-01

A newly devised procedure of prediction analysis, which is a linearized version of the nonlinear least squares method combined with the maximum entropy spectral analysis method, was proposed. This method was applied to time series data of measles case notification in several communities in the UK, USA and Denmark. The dominant spectral lines observed in each power spectral density (PSD) can be safely assigned as fundamental periods. The optimum least squares fitting (LSF) curve calculated using these fundamental periods can essentially reproduce the underlying variation of the measles data. An extension of the LSF curve can be used to predict measles case notification quantitatively. Some discussions including a predictability of chaotic time series are presented.

Toward an optimal solver for time-spectral fluid-dynamic and aeroelastic solutions on unstructured meshes

NASA Astrophysics Data System (ADS)

Mundis, Nathan L.; Mavriplis, Dimitri J.

2017-09-01

The time-spectral method applied to the Euler and coupled aeroelastic equations theoretically offers significant computational savings for purely periodic problems when compared to standard time-implicit methods. However, attaining superior efficiency with time-spectral methods over traditional time-implicit methods hinges on the ability rapidly to solve the large non-linear system resulting from time-spectral discretizations which become larger and stiffer as more time instances are employed or the period of the flow becomes especially short (i.e. the maximum resolvable wave-number increases). In order to increase the efficiency of these solvers, and to improve robustness, particularly for large numbers of time instances, the Generalized Minimal Residual Method (GMRES) is used to solve the implicit linear system over all coupled time instances. The use of GMRES as the linear solver makes time-spectral methods more robust, allows them to be applied to a far greater subset of time-accurate problems, including those with a broad range of harmonic content, and vastly improves the efficiency of time-spectral methods. In previous work, a wave-number independent preconditioner that mitigates the increased stiffness of the time-spectral method when applied to problems with large resolvable wave numbers has been developed. This preconditioner, however, directly inverts a large matrix whose size increases in proportion to the number of time instances. As a result, the computational time of this method scales as the cube of the number of time instances. In the present work, this preconditioner has been reworked to take advantage of an approximate-factorization approach that effectively decouples the spatial and temporal systems. Once decoupled, the time-spectral matrix can be inverted in frequency space, where it has entries only on the main diagonal and therefore can be inverted quite efficiently. This new GMRES/preconditioner combination is shown to be over an order of magnitude more efficient than the previous wave-number independent preconditioner for problems with large numbers of time instances and/or large reduced frequencies.

Development and application of the maximum entropy method and other spectral estimation techniques

NASA Astrophysics Data System (ADS)

King, W. R.

1980-09-01

This summary report is a collection of four separate progress reports prepared under three contracts, which are all sponsored by the Office of Naval Research in Arlington, Virginia. This report contains the results of investigations into the application of the maximum entropy method (MEM), a high resolution, frequency and wavenumber estimation technique. The report also contains a description of two, new, stable, high resolution spectral estimation techniques that is provided in the final report section. Many examples of wavenumber spectral patterns for all investigated techniques are included throughout the report. The maximum entropy method is also known as the maximum entropy spectral analysis (MESA) technique, and both names are used in the report. Many MEM wavenumber spectral patterns are demonstrated using both simulated and measured radar signal and noise data. Methods for obtaining stable MEM wavenumber spectra are discussed, broadband signal detection using the MEM prediction error transform (PET) is discussed, and Doppler radar narrowband signal detection is demonstrated using the MEM technique. It is also shown that MEM cannot be applied to randomly sampled data. The two new, stable, high resolution, spectral estimation techniques discussed in the final report section, are named the Wiener-King and the Fourier spectral estimation techniques. The two new techniques have a similar derivation based upon the Wiener prediction filter, but the two techniques are otherwise quite different. Further development of the techniques and measurement of the technique spectral characteristics is recommended for subsequent investigation.

Stability analysis of spectral methods for hyperbolic initial-boundary value systems

NASA Technical Reports Server (NTRS)

Gottlieb, D.; Lustman, L.; Tadmor, E.

1986-01-01

A constant coefficient hyperbolic system in one space variable, with zero initial data is discussed. Dissipative boundary conditions are imposed at the two points x = + or - 1. This problem is discretized by a spectral approximation in space. Sufficient conditions under which the spectral numerical solution is stable are demonstrated - moreover, these conditions have to be checked only for scalar equations. The stability theorems take the form of explicit bounds for the norm of the solution in terms of the boundary data. The dependence of these bounds on N, the number of points in the domain (or equivalently the degree of the polynomials involved), is investigated for a class of standard spectral methods, including Chebyshev and Legendre collocations.

Spectroradiometric calibration of the Thematic Mapper and Multispectral Scanner system. [White Sands, New Mexico

NASA Technical Reports Server (NTRS)

Palmer, J. M. (Principal Investigator); Slater, P. N.

1984-01-01

The newly built Caste spectropolarimeters gave satisfactory performance during tests in the solar radiometer and helicopter modes. A bandwidth normalization technique based on analysis of the moments of the spectral responsivity curves was used to analyze the spectral bands of the MSS and TM subsystems of LANDSAT 4 and 5 satellites. Results include the effective wavelength, the bandpass, the wavelength limits, and the normalized responsivity for each spectral channel. Temperature coefficients for TM PF channel 6 were also derived. The moments normalization method used yields sensor parameters whose derivation is independent of source characteristics (i.e., incident solar spectral irradiance, atmospheric transmittance, or ground reflectance). The errors expected using these parameters are lower than those expected using other normalization methods.

Evolutionary Computing Methods for Spectral Retrieval

NASA Technical Reports Server (NTRS)

Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

2009-01-01

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

New Operational Matrices for Solving Fractional Differential Equations on the Half-Line

PubMed Central

2015-01-01

In this paper, the fractional-order generalized Laguerre operational matrices (FGLOM) of fractional derivatives and fractional integration are derived. These operational matrices are used together with spectral tau method for solving linear fractional differential equations (FDEs) of order ν (0 < ν < 1) on the half line. An upper bound of the absolute errors is obtained for the approximate and exact solutions. Fractional-order generalized Laguerre pseudo-spectral approximation is investigated for solving nonlinear initial value problem of fractional order ν. The extension of the fractional-order generalized Laguerre pseudo-spectral method is given to solve systems of FDEs. We present the advantages of using the spectral schemes based on fractional-order generalized Laguerre functions and compare them with other methods. Several numerical examples are implemented for FDEs and systems of FDEs including linear and nonlinear terms. We demonstrate the high accuracy and the efficiency of the proposed techniques. PMID:25996369

New operational matrices for solving fractional differential equations on the half-line.

PubMed

Bhrawy, Ali H; Taha, Taha M; Alzahrani, Ebraheem O; Alzahrani, Ebrahim O; Baleanu, Dumitru; Alzahrani, Abdulrahim A

2015-01-01

In this paper, the fractional-order generalized Laguerre operational matrices (FGLOM) of fractional derivatives and fractional integration are derived. These operational matrices are used together with spectral tau method for solving linear fractional differential equations (FDEs) of order ν (0 < ν < 1) on the half line. An upper bound of the absolute errors is obtained for the approximate and exact solutions. Fractional-order generalized Laguerre pseudo-spectral approximation is investigated for solving nonlinear initial value problem of fractional order ν. The extension of the fractional-order generalized Laguerre pseudo-spectral method is given to solve systems of FDEs. We present the advantages of using the spectral schemes based on fractional-order generalized Laguerre functions and compare them with other methods. Several numerical examples are implemented for FDEs and systems of FDEs including linear and nonlinear terms. We demonstrate the high accuracy and the efficiency of the proposed techniques.

Nearest clusters based partial least squares discriminant analysis for the classification of spectral data.

PubMed

Song, Weiran; Wang, Hui; Maguire, Paul; Nibouche, Omar

2018-06-07

Partial Least Squares Discriminant Analysis (PLS-DA) is one of the most effective multivariate analysis methods for spectral data analysis, which extracts latent variables and uses them to predict responses. In particular, it is an effective method for handling high-dimensional and collinear spectral data. However, PLS-DA does not explicitly address data multimodality, i.e., within-class multimodal distribution of data. In this paper, we present a novel method termed nearest clusters based PLS-DA (NCPLS-DA) for addressing the multimodality and nonlinearity issues explicitly and improving the performance of PLS-DA on spectral data classification. The new method applies hierarchical clustering to divide samples into clusters and calculates the corresponding centre of every cluster. For a given query point, only clusters whose centres are nearest to such a query point are used for PLS-DA. Such a method can provide a simple and effective tool for separating multimodal and nonlinear classes into clusters which are locally linear and unimodal. Experimental results on 17 datasets, including 12 UCI and 5 spectral datasets, show that NCPLS-DA can outperform 4 baseline methods, namely, PLS-DA, kernel PLS-DA, local PLS-DA and k-NN, achieving the highest classification accuracy most of the time. Copyright © 2018 Elsevier B.V. All rights reserved.

A complex guided spectral transform Lanczos method for studying quantum resonance states

DOE PAGES

Yu, Hua-Gen

2014-12-28

A complex guided spectral transform Lanczos (cGSTL) algorithm is proposed to compute both bound and resonance states including energies, widths and wavefunctions. The algorithm comprises of two layers of complex-symmetric Lanczos iterations. A short inner layer iteration produces a set of complex formally orthogonal Lanczos (cFOL) polynomials. They are used to span the guided spectral transform function determined by a retarded Green operator. An outer layer iteration is then carried out with the transform function to compute the eigen-pairs of the system. The guided spectral transform function is designed to have the same wavefunctions as the eigenstates of the originalmore » Hamiltonian in the spectral range of interest. Therefore the energies and/or widths of bound or resonance states can be easily computed with their wavefunctions or by using a root-searching method from the guided spectral transform surface. The new cGSTL algorithm is applied to bound and resonance states of HO₂, and compared to previous calculations.« less

A general spectral transformation simultaneously including a Fourier transformation and a Laplace transformation

NASA Technical Reports Server (NTRS)

Marko, H.

1978-01-01

A general spectral transformation is proposed and described. Its spectrum can be interpreted as a Fourier spectrum or a Laplace spectrum. The laws and functions of the method are discussed in comparison with the known transformations, and a sample application is shown.

Methods for determining the physiological state of a plant

DOEpatents

Kramer, David M.; Sacksteder, Colette

2003-09-23

The present invention provides methods for measuring a photosynthetic parameter. The methods of the invention include the steps of: (a) illuminating a plant leaf until steady-state photosynthesis is achieved; (b) subjecting the illuminated plant leaf to a period of darkness; (c) using a kinetic spectrophotometer or kinetic spectrophotometer/fluorimeter to collect spectral data from the plant leaf treated in accordance with steps (a) and (b); and (d) determining a photosynthetic parameter from the spectral data. In another aspect, the invention provides methods for determining the physiological state of a plant.

Atmospheric turbulence profiling with unknown power spectral density

NASA Astrophysics Data System (ADS)

Helin, Tapio; Kindermann, Stefan; Lehtonen, Jonatan; Ramlau, Ronny

2018-04-01

Adaptive optics (AO) is a technology in modern ground-based optical telescopes to compensate for the wavefront distortions caused by atmospheric turbulence. One method that allows to retrieve information about the atmosphere from telescope data is so-called SLODAR, where the atmospheric turbulence profile is estimated based on correlation data of Shack-Hartmann wavefront measurements. This approach relies on a layered Kolmogorov turbulence model. In this article, we propose a novel extension of the SLODAR concept by including a general non-Kolmogorov turbulence layer close to the ground with an unknown power spectral density. We prove that the joint estimation problem of the turbulence profile above ground simultaneously with the unknown power spectral density at the ground is ill-posed and propose three numerical reconstruction methods. We demonstrate by numerical simulations that our methods lead to substantial improvements in the turbulence profile reconstruction compared to the standard SLODAR-type approach. Also, our methods can accurately locate local perturbations in non-Kolmogorov power spectral densities.

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.

Evaluating the utility of mid-infrared spectral subspaces for predicting soil properties.

PubMed

Sila, Andrew M; Shepherd, Keith D; Pokhariyal, Ganesh P

2016-04-15

We propose four methods for finding local subspaces in large spectral libraries. The proposed four methods include (a) cosine angle spectral matching; (b) hit quality index spectral matching; (c) self-organizing maps and (d) archetypal analysis methods. Then evaluate prediction accuracies for global and subspaces calibration models. These methods were tested on a mid-infrared spectral library containing 1907 soil samples collected from 19 different countries under the Africa Soil Information Service project. Calibration models for pH, Mehlich-3 Ca, Mehlich-3 Al, total carbon and clay soil properties were developed for the whole library and for the subspace. Root mean square error of prediction was used to evaluate predictive performance of subspace and global models. The root mean square error of prediction was computed using a one-third-holdout validation set. Effect of pretreating spectra with different methods was tested for 1st and 2nd derivative Savitzky-Golay algorithm, multiplicative scatter correction, standard normal variate and standard normal variate followed by detrending methods. In summary, the results show that global models outperformed the subspace models. We, therefore, conclude that global models are more accurate than the local models except in few cases. For instance, sand and clay root mean square error values from local models from archetypal analysis method were 50% poorer than the global models except for subspace models obtained using multiplicative scatter corrected spectra with which were 12% better. However, the subspace approach provides novel methods for discovering data pattern that may exist in large spectral libraries.

Determination of tailored filter sets to create rayfiles including spatial and angular resolved spectral information.

PubMed

Rotscholl, Ingo; Trampert, Klaus; Krüger, Udo; Perner, Martin; Schmidt, Franz; Neumann, Cornelius

2015-11-16

To simulate and optimize optical designs regarding perceived color and homogeneity in commercial ray tracing software, realistic light source models are needed. Spectral rayfiles provide angular and spatial varying spectral information. We propose a spectral reconstruction method with a minimum of time consuming goniophotometric near field measurements with optical filters for the purpose of creating spectral rayfiles. Our discussion focuses on the selection of the ideal optical filter combination for any arbitrary spectrum out of a given filter set by considering measurement uncertainties with Monte Carlo simulations. We minimize the simulation time by a preselection of all filter combinations, which bases on factorial design.

The Ultracool Typing Kit - An Open-Source, Qualitative Spectral Typing GUI for L Dwarfs

NASA Astrophysics Data System (ADS)

Schwab, Ellianna; Cruz, Kelle; Núñez, Alejandro; Burgasser, Adam J.; Rice, Emily; Reid, Neill; Faherty, Jacqueline K.; BDNYC

2018-01-01

The Ultracool Typing Kit (UTK) is an open-source graphical user interface for classifying the NIR spectral types of L dwarfs, including field and low-gravity dwarfs spanning L0-L9. The user is able to input an NIR spectrum and qualitatively compare the input spectrum to a full suite of spectral templates, including low-gravity beta and gamma templates. The user can choose to view the input spectrum as both a band-by-band comparison with the templates and a full bandwidth comparison with NIR spectral standards. Once an optimal qualitative comparison is selected, the user can save their spectral type selection both graphically and to a database. Using UTK to classify 78 previously typed L dwarfs, we show that a band-by-band classification method more accurately agrees with optical spectral typing systems than previous L dwarf NIR classification schemes. UTK is written in python, released on Zenodo with a BSD-3 clause license and publicly available on the BDNYC Github page.

The demodulated band transform

PubMed Central

Kovach, Christopher K.; Gander, Phillip E.

2016-01-01

Background Windowed Fourier decompositions (WFD) are widely used in measuring stationary and non-stationary spectral phenomena and in describing pairwise relationships among multiple signals. Although a variety of WFDs see frequent application in electrophysiological research, including the short-time Fourier transform, continuous wavelets, band-pass filtering and multitaper-based approaches, each carries certain drawbacks related to computational efficiency and spectral leakage. This work surveys the advantages of a WFD not previously applied in electrophysiological settings. New Methods A computationally efficient form of complex demodulation, the demodulated band transform (DBT), is described. Results DBT is shown to provide an efficient approach to spectral estimation with minimal susceptibility to spectral leakage. In addition, it lends itself well to adaptive filtering of non-stationary narrowband noise. Comparison with existing methods A detailed comparison with alternative WFDs is offered, with an emphasis on the relationship between DBT and Thomson's multitaper. DBT is shown to perform favorably in combining computational efficiency with minimal introduction of spectral leakage. Conclusion DBT is ideally suited to efficient estimation of both stationary and non-stationary spectral and cross-spectral statistics with minimal susceptibility to spectral leakage. These qualities are broadly desirable in many settings. PMID:26711370

Using spectral methods to obtain particle size information from optical data: applications to measurements from CARES 2010

NASA Astrophysics Data System (ADS)

Atkinson, Dean B.; Pekour, Mikhail; Chand, Duli; Radney, James G.; Kolesar, Katheryn R.; Zhang, Qi; Setyan, Ari; O'Neill, Norman T.; Cappa, Christopher D.

2018-04-01

Multi-wavelength in situ aerosol extinction, absorption and scattering measurements made at two ground sites during the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are analyzed using a spectral deconvolution method that allows extraction of particle-size-related information, including the fraction of extinction produced by the fine-mode particles and the effective radius of the fine mode. The spectral deconvolution method is typically applied to analysis of remote sensing measurements. Here, its application to in situ measurements allows for comparison with more direct measurement methods and validation of the retrieval approach. Overall, the retrieved fine-mode fraction and effective radius compare well with other in situ measurements, including size distribution measurements and scattering and absorption measurements made separately for PM1 and PM10, although there were some periods during which the different methods yielded different results. One key contributor to differences between the results obtained is the alternative, spectrally based definitions of fine and coarse modes from the optical methods, relative to instruments that use a physically defined cut point. These results indicate that for campaigns where size, composition and multi-wavelength optical property measurements are made, comparison of the results can result in closure or can identify unusual circumstances. The comparison here also demonstrates that in situ multi-wavelength optical property measurements can be used to determine information about particle size distributions in situations where direct size distribution measurements are not available.

Using spectral methods to obtain particle size information from optical data: applications to measurements from CARES 2010

DOE PAGES

Atkinson, Dean B.; Pekour, Mikhail; Chand, Duli; ...

2018-04-23

Here, multi-wavelength in situ aerosol extinction, absorption and scattering measurements made at two ground sites during the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are analyzed using a spectral deconvolution method that allows extraction of particle-size-related information, including the fraction of extinction produced by the fine-mode particles and the effective radius of the fine mode. The spectral deconvolution method is typically applied to analysis of remote sensing measurements. Here, its application to in situ measurements allows for comparison with more direct measurement methods and validation of the retrieval approach. Overall, the retrieved fine-mode fraction and effective radius compare wellmore » with other in situ measurements, including size distribution measurements and scattering and absorption measurements made separately for PM 1 and PM 10, although there were some periods during which the different methods yielded different results. One key contributor to differences between the results obtained is the alternative, spectrally based definitions of fine and coarse modes from the optical methods, relative to instruments that use a physically defined cut point. These results indicate that for campaigns where size, composition and multi-wavelength optical property measurements are made, comparison of the results can result in closure or can identify unusual circumstances. The comparison here also demonstrates that in situ multi-wavelength optical property measurements can be used to determine information about particle size distributions in situations where direct size distribution measurements are not available.« less

Using spectral methods to obtain particle size information from optical data: applications to measurements from CARES 2010

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

Atkinson, Dean B.; Pekour, Mikhail; Chand, Duli

Here, multi-wavelength in situ aerosol extinction, absorption and scattering measurements made at two ground sites during the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are analyzed using a spectral deconvolution method that allows extraction of particle-size-related information, including the fraction of extinction produced by the fine-mode particles and the effective radius of the fine mode. The spectral deconvolution method is typically applied to analysis of remote sensing measurements. Here, its application to in situ measurements allows for comparison with more direct measurement methods and validation of the retrieval approach. Overall, the retrieved fine-mode fraction and effective radius compare wellmore » with other in situ measurements, including size distribution measurements and scattering and absorption measurements made separately for PM 1 and PM 10, although there were some periods during which the different methods yielded different results. One key contributor to differences between the results obtained is the alternative, spectrally based definitions of fine and coarse modes from the optical methods, relative to instruments that use a physically defined cut point. These results indicate that for campaigns where size, composition and multi-wavelength optical property measurements are made, comparison of the results can result in closure or can identify unusual circumstances. The comparison here also demonstrates that in situ multi-wavelength optical property measurements can be used to determine information about particle size distributions in situations where direct size distribution measurements are not available.« less

Using spectral methods to obtain particle size information from optical data: applications to measurements from CARES 2010

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

Atkinson, Dean B.; Pekour, Mikhail; Chand, Duli

Multi-wavelength in situ aerosol extinction, absorption and scattering measurements made at two ground sites during the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are analyzed using a spectral deconvolution method that allows extraction of particle-size-related information, including the fraction of extinction produced by the fine-mode particles and the effective radius of the fine mode. The spectral deconvolution method is typically applied to analysis of remote sensing measurements. Here, its application to in situ measurements allows for comparison with more direct measurement methods and validation of the retrieval approach. Overall, the retrieved fine-mode fraction and effective radius compare well withmore » other in situ measurements, including size distribution measurements and scattering and absorption measurements made separately for PM 1 and PM 10, although there were some periods during which the different methods yielded different results. One key contributor to differences between the results obtained is the alternative, spectrally based definitions of fine and coarse modes from the optical methods, relative to instruments that use a physically defined cut point. These results indicate that for campaigns where size, composition and multi-wavelength optical property measurements are made, comparison of the results can result in closure or can identify unusual circumstances. The comparison here also demonstrates that in situ multi-wavelength optical property measurements can be used to determine information about particle size distributions in situations where direct size distribution measurements are not available.« less

Determination of particles concentration in Black Sea waters from spectral beam attenuation coefficient

NASA Astrophysics Data System (ADS)

Korchemkina, E. N.; Latushkin, A. A.; Lee, M. E.

2017-11-01

The methods of determination of concentration and scattering by suspended particles in seawater are compared. The methods considered include gravimetric measurements of the mass concentration of suspended matter, empirical and analytical calculations based on measurements of the light beam attenuation coefficient (BAC) in 4 spectral bands, calculation of backscattering by particles using satellite measurements in the visible spectral range. The data were obtained in two cruises of the R/V "Professor Vodyanitsky" in the deep-water part of the Black Sea in July and October 2016., Spatial distribution of scattering by marine particles according to satellite data is in good agreement with the contact measurements.

A comparison of digital multi-spectral imagery versus conventional photography for mapping seagrass in Indian River Lagoon, Florida

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

Virnstein, R.; Tepera, M.; Beazley, L.

1997-06-01

A pilot study is very briefly summarized in the article. The study tested the potential of multi-spectral digital imagery for discrimination of seagrass densities and species, algae, and bottom types. Imagery was obtained with the Compact Airborne Spectral Imager (casi) and two flight lines flown with hyper-spectral mode. The photogrammetric method used allowed interpretation of the highest quality product, eliminating limitations caused by outdated or poor quality base maps and the errors associated with transfer of polygons. Initial image analysis indicates that the multi-spectral imagery has several advantages, including sophisticated spectral signature recognition and classification, ease of geo-referencing, and rapidmore » mosaicking.« less

Novel hyperspectral prediction method and apparatus

NASA Astrophysics Data System (ADS)

Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

2009-05-01

Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

Implementation of spectral clustering on microarray data of carcinoma using k-means algorithm

NASA Astrophysics Data System (ADS)

Frisca, Bustamam, Alhadi; Siswantining, Titin

2017-03-01

Clustering is one of data analysis methods that aims to classify data which have similar characteristics in the same group. Spectral clustering is one of the most popular modern clustering algorithms. As an effective clustering technique, spectral clustering method emerged from the concepts of spectral graph theory. Spectral clustering method needs partitioning algorithm. There are some partitioning methods including PAM, SOM, Fuzzy c-means, and k-means. Based on the research that has been done by Capital and Choudhury in 2013, when using Euclidian distance k-means algorithm provide better accuracy than PAM algorithm. So in this paper we use k-means as our partition algorithm. The major advantage of spectral clustering is in reducing data dimension, especially in this case to reduce the dimension of large microarray dataset. Microarray data is a small-sized chip made of a glass plate containing thousands and even tens of thousands kinds of genes in the DNA fragments derived from doubling cDNA. Application of microarray data is widely used to detect cancer, for the example is carcinoma, in which cancer cells express the abnormalities in his genes. The purpose of this research is to classify the data that have high similarity in the same group and the data that have low similarity in the others. In this research, Carcinoma microarray data using 7457 genes. The result of partitioning using k-means algorithm is two clusters.

[Research on spatially modulated Fourier transform imaging spectrometer data processing method].

PubMed

Huang, Min; Xiangli, Bin; Lü, Qun-Bo; Zhou, Jin-Song; Jing, Juan-Juan; Cui, Yan

2010-03-01

Fourier transform imaging spectrometer is a new technic, and has been developed very rapidly in nearly ten years. The data catched by Fourier transform imaging spectrometer is indirect data, can not be used by user, and need to be processed by various approaches, including data pretreatment, apodization, phase correction, FFT, and spectral radicalization calibration. No paper so far has been found roundly to introduce this method. In the present paper, the author will give an effective method to process the interfering data to spectral data, and with this method we can obtain good result.

SpectralNET – an application for spectral graph analysis and visualization

PubMed Central

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-01-01

Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from . Source code is available upon request. PMID:16236170

SpectralNET--an application for spectral graph analysis and visualization.

PubMed

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-10-19

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.

Micro spectrometer for parallel light and method of use

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); Choi, Sang H. (Inventor); King, Glen C. (Inventor); Elliott, James R. (Inventor)

2011-01-01

A spectrometer system includes an optical assembly for collimating light, a micro-ring grating assembly having a plurality of coaxially-aligned ring gratings, an aperture device defining an aperture circumscribing a target focal point, and a photon detector. An electro-optical layer of the grating assembly may be electrically connected to an energy supply to change the refractive index of the electro-optical layer. Alternately, the gratings may be electrically connected to the energy supply and energized, e.g., with alternating voltages, to change the refractive index. A data recorder may record the predetermined spectral characteristic. A method of detecting a spectral characteristic of a predetermined wavelength of source light includes generating collimated light using an optical assembly, directing the collimated light onto the micro-ring grating assembly, and selectively energizing the micro-ring grating assembly to diffract the predetermined wavelength onto the target focal point, and detecting the spectral characteristic using a photon detector.

The analytical design of spectral measurements for multispectral remote sensor systems

NASA Technical Reports Server (NTRS)

Wiersma, D. J.; Landgrebe, D. A. (Principal Investigator)

1979-01-01

The author has identified the following significant results. In order to choose a design which will be optimal for the largest class of remote sensing problems, a method was developed which attempted to represent the spectral response function from a scene as accurately as possible. The performance of the overall recognition system was studied relative to the accuracy of the spectral representation. The spectral representation was only one of a set of five interrelated parameter categories which also included the spatial representation parameter, the signal to noise ratio, ancillary data, and information classes. The spectral response functions observed from a stratum were modeled as a stochastic process with a Gaussian probability measure. The criterion for spectral representation was defined by the minimum expected mean-square error.

Temperature Distribution in a Composite of Opaque and Semitransparent Spectral Layers

NASA Technical Reports Server (NTRS)

Siegel, Robert

1997-01-01

The analysis of radiative transfer becomes computationally complex for a composite when there are multiple layers and multiple spectral bands. A convenient analytical method is developed for combined radiation and conduction in a composite of alternating semitransparent and opaque layers. The semi- transparent layers absorb, scatter, and emit radiation, and spectral properties with large scattering are included. The two-flux method is used, and its applicability is verified by comparison with a basic solution in the literature. The differential equation in the two-flux method Is solved by deriving a Green's function. The solution technique is applied to analyze radiation effects in a multilayer zirconia thermal barrier coating with internal radiation shields for conditions in an aircraft engine combustor. The zirconia radiative properties are modeled by two spectral bands. Thin opaque layers within the coating are used to decrease radiant transmission that can degrade the zirconia insulating ability. With radiation shields, the temperature distributions more closely approach the opaque limit that provides the lowest metal wall temperatures.

Extension of the Time-Spectral Approach to Overset Solvers for Arbitrary Motion

NASA Technical Reports Server (NTRS)

Leffell, Joshua Isaac; Murman, Scott M.; Pulliam, Thomas H.

2012-01-01

Forced periodic flows arise in a broad range of aerodynamic applications such as rotorcraft, turbomachinery, and flapping wing configurations. Standard practice involves solving the unsteady flow equations forward in time until the initial transient exits the domain and a statistically stationary flow is achieved. It is often required to simulate through several periods to remove the initial transient making unsteady design optimization prohibitively expensive for most realistic problems. An effort to reduce the computational cost of these calculations led to the development of the Harmonic Balance method [1, 2] which capitalizes on the periodic nature of the solution. The approach exploits the fact that forced temporally periodic flow, while varying in the time domain, is invariant in the frequency domain. Expanding the temporal variation at each spatial node into a Fourier series transforms the unsteady governing equations into a steady set of equations in integer harmonics that can be tackled with the acceleration techniques afforded to steady-state flow solvers. Other similar approaches, such as the Nonlinear Frequency Domain [3,4,5], Reduced Frequency [6] and Time-Spectral [7, 8, 9] methods, were developed shortly thereafter. Additionally, adjoint-based optimization techniques can be applied [10, 11] as well as frequency-adaptive methods [12, 13, 14] to provide even more flexibility to the method. The Fourier temporal basis functions imply spectral convergence as the number of harmonic modes, and correspondingly number of time samples, N, is increased. Some elect to solve the equations in the frequency domain directly, while others choose to transform the equations back into the time domain to simplify the process of adding this capability to existing solvers, but each harnesses the underlying steady solution in the frequency domain. These temporal projection methods will herein be collectively referred to as Time-Spectral methods. Time-Spectral methods have demonstrated marked success in reducing the computational costs associated with simulating periodic forced flows, but have yet to be fully applied to overset or Cartesian solvers for arbitrary motion with dynamic hole-cutting. Overset and Cartesian grid methodologies are versatile techniques capable of handling complex geometry configurations in practical engineering applications, and the combination of the Time-Spectral approach with this general capability potentially provides an enabling new design and analysis tool. In an arbitrary moving-body scenario for these approaches, a Lagrangian body moves through a fixed Eulerian mesh and mesh points in the Eulerian mesh interior to the solid body are removed (cut or blanked), leaving a hole in the Eulerian mesh. During the dynamic motion some gridpoints in the domain are blanked and do not have a complete set of time-samples preventing a direct implementation of the Time-Spectral method. Murman[6] demonstrated the Time-Spectral approach for a Cartesian solver with a rigid domain motion, wherein the hole cutting remains constant. Similarly, Custer et al. [15, 16] used the NASA overset OVERFLOW solver and limited the amount of relative motion to ensure static hole-cutting and interpolation. Recently, Mavriplis and Mundis[17] demonstrated a qualitative method for applying the Time-Spectral approach to an unstructured overset solver for arbitrary motion. The goal of the current work is to develop a robust and general method for handling arbitrary motion with the Time-Spectral approach within an overset or Cartesian mesh method, while still approaching the spectral convergence rate of the original Time-Spectral approach. The viscous OVERFLOW solver will be augmented with the new Time-Spectral algorithm and the capability of the method for benchmark problems in rotorcraft and turbomachinery will be demonstrated. This abstract begins with a brief synopsis of the Time-Spectral approach for overset grids and provides details of e current approach to allow for arbitrary motion. Model problem results in one and two dimensions are included to demonstrate the viability of the method and the convergence properties. Section IV briefly outlines the implementation into the OVERFLOW solver, and the abstract closes with a description of the benchmark test cases which will be included in the final paper.

Iterative spectral methods and spectral solutions to compressible flows

NASA Technical Reports Server (NTRS)

Hussaini, M. Y.; Zang, T. A.

1982-01-01

A spectral multigrid scheme is described which can solve pseudospectral discretizations of self-adjoint elliptic problems in O(N log N) operations. An iterative technique for efficiently implementing semi-implicit time-stepping for pseudospectral discretizations of Navier-Stokes equations is discussed. This approach can handle variable coefficient terms in an effective manner. Pseudospectral solutions of compressible flow problems are presented. These include one dimensional problems and two dimensional Euler solutions. Results are given both for shock-capturing approaches and for shock-fitting ones.

UV spectroscopy including ISM line absorption: of the exciting star of Abell 35

NASA Astrophysics Data System (ADS)

Ziegler, M.; Rauch, T.; Werner, K.; Kruk, J. W.

Reliable spectral analysis that is based on high-resolution UV observations requires an adequate, simultaneous modeling of the interstellar line absorption and reddening. In the case of the central star of the planetary nebula Abell 35, BD-22 3467, we demonstrate our current standard spectral-analysis method that is based on the Tübingen NLTE Model-Atmosphere Package (TMAP). We present an on- going spectral analysis of FUSE and HST/STIS observations of BD-22 3467.

Three-dimensional arbitrary voxel shapes in spectroscopy with submillisecond TEs.

PubMed

Snyder, Jeff; Haas, Martin; Dragonu, Iulius; Hennig, Jürgen; Zaitsev, Maxim

2012-08-01

A novel spectroscopic method for submillisecond TEs and three-dimensional arbitrarily shaped voxels was developed and applied to phantom and in vivo measurements, with additional parallel excitation (PEX) implementation. A segmented spherical shell excitation trajectory was used in combination with appropriate radiofrequency weights for target selection in three dimensions. Measurements in a two-compartment phantom realized a TE of 955 µs, excellent spectral quality and comparable signal-to-noise ratios between accelerated (R = 2) and nonaccelerated modes. The two-compartment model allowed a comparison of the spectral suppression qualities of the method and, although outer volume signals were suppressed by factors of 1434 and 2246 compared with the theoretical unsuppressed case for the clinical and PEX modes, respectively, incomplete suppression of the outer volume (935 cm(3) compared with a target volume of 5.86 cm(3) ) resulted in a spectral contamination of 10.2% and 6.5% compared with the total signal. The method was also demonstrated in vivo in human brain on a clinical system at TE = 935 µs with good signal-to-noise ratio and spatial and spectral selection, and included LCModel relative quantification analysis. Eight metabolites showed significant fitting accuracy, including aspartate, N-acetylaspartylglutamate, glutathione and glutamate. Copyright © 2012 John Wiley & Sons, Ltd.

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.

Film thickness measurement based on nonlinear phase analysis using a Linnik microscopic white-light spectral interferometer.

PubMed

Guo, Tong; Chen, Zhuo; Li, Minghui; Wu, Juhong; Fu, Xing; Hu, Xiaotang

2018-04-20

Based on white-light spectral interferometry and the Linnik microscopic interference configuration, the nonlinear phase components of the spectral interferometric signal were analyzed for film thickness measurement. The spectral interferometric signal was obtained using a Linnik microscopic white-light spectral interferometer, which includes the nonlinear phase components associated with the effective thickness, the nonlinear phase error caused by the double-objective lens, and the nonlinear phase of the thin film itself. To determine the influence of the effective thickness, a wavelength-correction method was proposed that converts the effective thickness into a constant value; the nonlinear phase caused by the effective thickness can then be determined and subtracted from the total nonlinear phase. A method for the extraction of the nonlinear phase error caused by the double-objective lens was also proposed. Accurate thickness measurement of a thin film can be achieved by fitting the nonlinear phase of the thin film after removal of the nonlinear phase caused by the effective thickness and by the nonlinear phase error caused by the double-objective lens. The experimental results demonstrated that both the wavelength-correction method and the extraction method for the nonlinear phase error caused by the double-objective lens improve the accuracy of film thickness measurements.

Identifying scales of pattern in ecological data: a comparison of lacunarity, spectral and wavelet analyses

Treesearch

Sari C. Saunders; Jiquan Chen; Thomas D. Drummer; Eric J. Gustafson; Kimberley D. Brosofske

2005-01-01

Identifying scales of pattern in ecological systems and coupling patterns to processes that create them are ongoing challenges. We examined the utility of three techniques (lacunarity, spectral, and wavelet analysis) for detecting scales of pattern of ecological data. We compared the information obtained using these methods for four datasets, including: surface...

High-Order Methods for Computational Fluid Dynamics: A Brief Review of Compact Differential Formulations on Unstructured Grids

NASA Technical Reports Server (NTRS)

Huynh, H. T.; Wang, Z. J.; Vincent, P. E.

2013-01-01

Popular high-order schemes with compact stencils for Computational Fluid Dynamics (CFD) include Discontinuous Galerkin (DG), Spectral Difference (SD), and Spectral Volume (SV) methods. The recently proposed Flux Reconstruction (FR) approach or Correction Procedure using Reconstruction (CPR) is based on a differential formulation and provides a unifying framework for these high-order schemes. Here we present a brief review of recent developments for the FR/CPR schemes as well as some pacing items.

A novel spectral resolution and simultaneous determination of multicomponent mixture of Vitamins B1, B6, B12, Benfotiamine and Diclofenac in tablets and capsules by derivative and MCR-ALS

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Abdelwahab, Nada S.; Fayed, Ahmed S.

2015-04-01

A novel method was developed for spectral resolution and further determination of five-component mixture including Vitamin B complex (B1, B6, B12 and Benfotiamine) along with the commonly co-formulated Diclofenac. The method is simple, sensitive, precise and could efficiently determine the five components by a complementary application of two different techniques. The first is univariate second derivative method that was successfully applied for determination of Vitamin B12. The second is Multivariate Curve Resolution using the Alternating Least Squares method (MCR-ALS) by which an efficient resolution and quantitation of the quaternary spectrally overlapped Vitamin B1, Vitamin B6, Benfotiamine and Diclofenac sodium were achieved. The effect of different constraints was studied and the correlation between the true spectra and the estimated spectral profiles were found to be 0.9998, 0.9983, 0.9993 and 0.9933 for B1, B6, Benfotiamine and Diclofenac, respectively. All components were successfully determined in tablets and capsules and the results were compared to HPLC methods and they were found to be statistically non-significant.

Evaluation of Mandarin Chinese Speech Recognition in Adults with Cochlear Implants Using the Spectral Ripple Discrimination Test

PubMed Central

Dai, Chuanfu; Zhao, Zeqi; Zhang, Duo; Lei, Guanxiong

2018-01-01

Background The aim of this study was to explore the value of the spectral ripple discrimination test in speech recognition evaluation among a deaf (post-lingual) Mandarin-speaking population in China following cochlear implantation. Material/Methods The study included 23 Mandarin-speaking adult subjects with normal hearing (normal-hearing group) and 17 deaf adults who were former Mandarin-speakers, with cochlear implants (cochlear implantation group). The normal-hearing subjects were divided into men (n=10) and women (n=13). The spectral ripple discrimination thresholds between the groups were compared. The correlation between spectral ripple discrimination thresholds and Mandarin speech recognition rates in the cochlear implantation group were studied. Results Spectral ripple discrimination thresholds did not correlate with age (r=−0.19; p=0.22), and there was no significant difference in spectral ripple discrimination thresholds between the male and female groups (p=0.654). Spectral ripple discrimination thresholds of deaf adults with cochlear implants were significantly correlated with monosyllabic recognition rates (r=0.84; p=0.000). Conclusions In a Mandarin Chinese speaking population, spectral ripple discrimination thresholds of normal-hearing individuals were unaffected by both gender and age. Spectral ripple discrimination thresholds were correlated with Mandarin monosyllabic recognition rates of Mandarin-speaking in post-lingual deaf adults with cochlear implants. The spectral ripple discrimination test is a promising method for speech recognition evaluation in adults following cochlear implantation in China. PMID:29806954

Evaluation of Mandarin Chinese Speech Recognition in Adults with Cochlear Implants Using the Spectral Ripple Discrimination Test.

PubMed

Dai, Chuanfu; Zhao, Zeqi; Shen, Weidong; Zhang, Duo; Lei, Guanxiong; Qiao, Yuehua; Yang, Shiming

2018-05-28

BACKGROUND The aim of this study was to explore the value of the spectral ripple discrimination test in speech recognition evaluation among a deaf (post-lingual) Mandarin-speaking population in China following cochlear implantation. MATERIAL AND METHODS The study included 23 Mandarin-speaking adult subjects with normal hearing (normal-hearing group) and 17 deaf adults who were former Mandarin-speakers, with cochlear implants (cochlear implantation group). The normal-hearing subjects were divided into men (n=10) and women (n=13). The spectral ripple discrimination thresholds between the groups were compared. The correlation between spectral ripple discrimination thresholds and Mandarin speech recognition rates in the cochlear implantation group were studied. RESULTS Spectral ripple discrimination thresholds did not correlate with age (r=-0.19; p=0.22), and there was no significant difference in spectral ripple discrimination thresholds between the male and female groups (p=0.654). Spectral ripple discrimination thresholds of deaf adults with cochlear implants were significantly correlated with monosyllabic recognition rates (r=0.84; p=0.000). CONCLUSIONS In a Mandarin Chinese speaking population, spectral ripple discrimination thresholds of normal-hearing individuals were unaffected by both gender and age. Spectral ripple discrimination thresholds were correlated with Mandarin monosyllabic recognition rates of Mandarin-speaking in post-lingual deaf adults with cochlear implants. The spectral ripple discrimination test is a promising method for speech recognition evaluation in adults following cochlear implantation in China.

Comparisons of a Constrained Least Squares Model versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

NASA Technical Reports Server (NTRS)

Abercromby, Kira J.; Rapp, Jason; Bedard, Donald; Seitzer, Patrick; Cardona, Tommaso; Cowardin, Heather; Barker, Ed; Lederer, Susan

2013-01-01

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University (Cal Poly) in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a reddening of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object s suspected material component will be discussed herein.

Comparisons of a Constrained Least Squares Model Versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

NASA Technical Reports Server (NTRS)

Rapp, Jason; Abercromby, Kira J.; Bedard, Donald; Seitzer, Patrick; Cardona, Tommaso; Cowardin, Heather; Barker, Ed; Lederer, Susan

2012-01-01

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a "reddening" of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object's suspected material component will be discussed herein.

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

NASA Astrophysics Data System (ADS)

An, G. Q.

2018-04-01

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

Rapid Chemometric Filtering of Spectral Data

NASA Technical Reports Server (NTRS)

Beaman, Gregory; Pelletier, Michael; Seshadri, Suresh

2004-01-01

A method of rapid, programmable filtering of spectral transmittance, reflectance, or fluorescence data to measure the concentrations of chemical species has been proposed. By programmable is meant that a variety of spectral analyses can readily be performed and modified in software, firmware, and/or electronic hardware, without need to change optical filters or other optical hardware of the associated spectrometers. The method is intended to enable real-time identification of single or multiple target chemical species in applications that involve high-throughput screening of multiple samples. Examples of such applications include (but are not limited to) combinatorial chemistry, flow cytometry, bead assays, testing drugs, remote sensing, and identification of targets. The basic concept of the proposed method is to perform real-time crosscorrelations of a measured spectrum with one or more analytical function(s) of wavelength that could be, for example, the known spectra of target species. Assuming that measured spectral intensities are proportional to concentrations of target species plus background spectral intensities, then after subtraction of background levels, it should be possible to determine target species concentrations from cross-correlation values. Of course, the problem of determining the concentrations is more complex when spectra of different species overlap, but the problem can be solved by use of multiple analytical functions in combination with computational techniques that have been developed previously for analyses of this type. The method is applicable to the design and operation of a spectrometer in which spectrally dispersed light is measured by means of an active-pixel sensor (APS) array. The row or column dimension of such an array is generally chosen to be aligned along the spectral-dispersion dimension, so that each pixel intercepts light in a narrow spectral band centered on a wavelength that is a known function of the pixel position. The proposed method admits of two hardware implementations for computing cross-correlations in real time.

Relationship between behavioral and physiological spectral-ripple discrimination.

PubMed

Won, Jong Ho; Clinard, Christopher G; Kwon, Seeyoun; Dasika, Vasant K; Nie, Kaibao; Drennan, Ward R; Tremblay, Kelly L; Rubinstein, Jay T

2011-06-01

Previous studies have found a significant correlation between spectral-ripple discrimination and speech and music perception in cochlear implant (CI) users. This relationship could be of use to clinicians and scientists who are interested in using spectral-ripple stimuli in the assessment and habilitation of CI users. However, previous psychoacoustic tasks used to assess spectral discrimination are not suitable for all populations, and it would be beneficial to develop methods that could be used to test all age ranges, including pediatric implant users. Additionally, it is important to understand how ripple stimuli are processed in the central auditory system and how their neural representation contributes to behavioral performance. For this reason, we developed a single-interval, yes/no paradigm that could potentially be used both behaviorally and electrophysiologically to estimate spectral-ripple threshold. In experiment 1, behavioral thresholds obtained using the single-interval method were compared to thresholds obtained using a previously established three-alternative forced-choice method. A significant correlation was found (r = 0.84, p = 0.0002) in 14 adult CI users. The spectral-ripple threshold obtained using the new method also correlated with speech perception in quiet and noise. In experiment 2, the effect of the number of vocoder-processing channels on the behavioral and physiological threshold in normal-hearing listeners was determined. Behavioral thresholds, using the new single-interval method, as well as cortical P1-N1-P2 responses changed as a function of the number of channels. Better behavioral and physiological performance (i.e., better discrimination ability at higher ripple densities) was observed as more channels added. In experiment 3, the relationship between behavioral and physiological data was examined. Amplitudes of the P1-N1-P2 "change" responses were significantly correlated with d' values from the single-interval behavioral procedure. Results suggest that the single-interval procedure with spectral-ripple phase inversion in ongoing stimuli is a valid approach for measuring behavioral or physiological spectral resolution.

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

A fast and well-conditioned spectral method for singular integral equations

NASA Astrophysics Data System (ADS)

Slevinsky, Richard Mikael; Olver, Sheehan

2017-03-01

We develop a spectral method for solving univariate singular integral equations over unions of intervals by utilizing Chebyshev and ultraspherical polynomials to reformulate the equations as almost-banded infinite-dimensional systems. This is accomplished by utilizing low rank approximations for sparse representations of the bivariate kernels. The resulting system can be solved in O (m2 n) operations using an adaptive QR factorization, where m is the bandwidth and n is the optimal number of unknowns needed to resolve the true solution. The complexity is reduced to O (mn) operations by pre-caching the QR factorization when the same operator is used for multiple right-hand sides. Stability is proved by showing that the resulting linear operator can be diagonally preconditioned to be a compact perturbation of the identity. Applications considered include the Faraday cage, and acoustic scattering for the Helmholtz and gravity Helmholtz equations, including spectrally accurate numerical evaluation of the far- and near-field solution. The JULIA software package SingularIntegralEquations.jl implements our method with a convenient, user-friendly interface.

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.

Individual Sensitivity to Spectral and Temporal Cues in Listeners With Hearing Impairment

PubMed Central

Wright, Richard A.; Blackburn, Michael C.; Tatman, Rachael; Gallun, Frederick J.

2015-01-01

Purpose The present study was designed to evaluate use of spectral and temporal cues under conditions in which both types of cues were available. Method Participants included adults with normal hearing and hearing loss. We focused on 3 categories of speech cues: static spectral (spectral shape), dynamic spectral (formant change), and temporal (amplitude envelope). Spectral and/or temporal dimensions of synthetic speech were systematically manipulated along a continuum, and recognition was measured using the manipulated stimuli. Level was controlled to ensure cue audibility. Discriminant function analysis was used to determine to what degree spectral and temporal information contributed to the identification of each stimulus. Results Listeners with normal hearing were influenced to a greater extent by spectral cues for all stimuli. Listeners with hearing impairment generally utilized spectral cues when the information was static (spectral shape) but used temporal cues when the information was dynamic (formant transition). The relative use of spectral and temporal dimensions varied among individuals, especially among listeners with hearing loss. Conclusion Information about spectral and temporal cue use may aid in identifying listeners who rely to a greater extent on particular acoustic cues and applying that information toward therapeutic interventions. PMID:25629388

Ship Detection Based on Multiple Features in Random Forest Model for Hyperspectral Images

NASA Astrophysics Data System (ADS)

Li, N.; Ding, L.; Zhao, H.; Shi, J.; Wang, D.; Gong, X.

2018-04-01

A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in the range of near infrared or short-wave infrared spectrum, is used to segment land and sea on Otsu threshold segmentation method. Secondly, multiple features that include spectral and texture features are extracted from hyperspectral images. Principal components analysis (PCA) is used to extract spectral features, the Grey Level Co-occurrence Matrix (GLCM) is used to extract texture features. Finally, Random Forest (RF) model is introduced to detect ships based on the extracted features. To illustrate the effectiveness of the method, we carry out experiments over the EO-1 data by comparing single feature and different multiple features. Compared with the traditional single feature method and Support Vector Machine (SVM) model, the proposed method can stably achieve the target detection of ships under complex background and can effectively improve the detection accuracy of ships.

ERTS-1 imagery and native plant distributions

NASA Technical Reports Server (NTRS)

Musick, H. B.; Mcginnies, W.; Haase, E.; Lepley, L. K.

1974-01-01

A method is developed for using ERTS spectral signature data to determine plant community distribution and phenology without resolving individual plants. An Exotech ERTS radiometer was used near ground level to obtain spectral signatures for a desert plant community, including two shrub species, ground covered with live annuals in April and dead ones in June, and bare ground. It is shown that comparisons of scene types can be made when spectral signatures are expressed as a ratio of red reflectivity to IR reflectivity or when they are plotted as red reflectivity vs. IR reflectivity, in which case the signature clusters of each component are more distinct. A method for correcting and converting the ERTS radiance values to reflectivity values for comparison with ground truth data is appended.

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.

Multi-spectral digital holographic microscopy for enhanced quantitative phase imaging of living cells

NASA Astrophysics Data System (ADS)

Kemper, Björn; Kastl, Lena; Schnekenburger, Jürgen; Ketelhut, Steffi

2018-02-01

Main restrictions of using laser light in digital holographic microscopy (DHM) are coherence induced noise and parasitic reflections in the experimental setup which limit resolution and measurement accuracy. We explored, if coherence properties of partial coherent light sources can be generated synthetically utilizing spectrally tunable lasers. The concept of the method is demonstrated by label-free quantitative phase imaging of living pancreatic tumor cells and utilizing an experimental configuration including a commercial microscope and a laser source with a broad tunable spectral range of more than 200 nm.

Higher-Order Spectral Analysis of F-18 Flight Flutter Data

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Dunn, Shane

2005-01-01

Royal Australian Air Force (RAAF) F/A-18 flight flutter test data is presented and analyzed using various techniques. The data includes high-quality measurements of forced responses and limit cycle oscillation (LCO) phenomena. Standard correlation and power spectral density (PSD) techniques are applied to the data and presented. Novel applications of experimentally-identified impulse responses and higher-order spectral techniques are also applied to the data and presented. The goal of this research is to develop methods that can identify the onset of nonlinear aeroelastic phenomena, such as LCO, during flutter testing.

Informed Source Separation of Atmospheric and Surface Signal Contributions in Shortwave Hyperspectral Imagery using Non-negative Matrix Factorization

NASA Astrophysics Data System (ADS)

Wright, L.; Coddington, O.; Pilewskie, P.

2015-12-01

Current challenges in Earth remote sensing require improved instrument spectral resolution, spectral coverage, and radiometric accuracy. Hyperspectral instruments, deployed on both aircraft and spacecraft, are a growing class of Earth observing sensors designed to meet these challenges. They collect large amounts of spectral data, allowing thorough characterization of both atmospheric and surface properties. The higher accuracy and increased spectral and spatial resolutions of new imagers require new numerical approaches for processing imagery and separating surface and atmospheric signals. One potential approach is source separation, which allows us to determine the underlying physical causes of observed changes. Improved signal separation will allow hyperspectral instruments to better address key science questions relevant to climate change, including land-use changes, trends in clouds and atmospheric water vapor, and aerosol characteristics. In this work, we investigate a Non-negative Matrix Factorization (NMF) method for the separation of atmospheric and land surface signal sources. NMF offers marked benefits over other commonly employed techniques, including non-negativity, which avoids physically impossible results, and adaptability, which allows the method to be tailored to hyperspectral source separation. We adapt our NMF algorithm to distinguish between contributions from different physically distinct sources by introducing constraints on spectral and spatial variability and by using library spectra to inform separation. We evaluate our NMF algorithm with simulated hyperspectral images as well as hyperspectral imagery from several instruments including, the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), NASA Hyperspectral Imager for the Coastal Ocean (HICO) and National Ecological Observatory Network (NEON) Imaging Spectrometer.

A Comparison of PSD Enveloping Methods for Nonstationary Vibration

NASA Technical Reports Server (NTRS)

Irvine, Tom

2015-01-01

There is a need to derive a power spectral density (PSD) envelope for nonstationary acceleration time histories, including launch vehicle data, so that components can be designed and tested accordingly. This paper presents the results of the three methods for an actual flight accelerometer record. Guidelines are given for the application of each method to nonstationary data. The method can be extended to other scenarios, including transportation vibration.

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Akbari, D.

2017-11-01

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

Method of improving a digital image

NASA Technical Reports Server (NTRS)

Jobson, Daniel J. (Inventor); Woodell, Glenn A. (Inventor); Rahman, Zia-ur (Inventor)

1999-01-01

A method of improving a digital image is provided. The image is initially represented by digital data indexed to represent positions on a display. The digital data is indicative of an intensity value I.sub.i (x,y) for each position (x,y) in each i-th spectral band. The intensity value for each position in each i-th spectral band is adjusted to generate an adjusted intensity value for each position in each i-th spectral band in accordance with ##EQU1## where S is the number of unique spectral bands included in said digital data, W.sub.n is a weighting factor and * denotes the convolution operator. Each surround function F.sub.n (x,y) is uniquely scaled to improve an aspect of the digital image, e.g., dynamic range compression, color constancy, and lightness rendition. The adjusted intensity value for each position in each i-th spectral band is filtered with a common function and then presented to a display device. For color images, a novel color restoration step is added to give the image true-to-life color that closely matches human observation.

Method and system for calibrating acquired spectra for use in spectral analysis

DOEpatents

Reber, Edward L.; Rohde, Kenneth W.; Blackwood, Larry G.

2010-09-14

A method for calibrating acquired spectra for use in spectral analysis includes performing Gaussian peak fitting to spectra acquired by a plurality of NaI detectors to define peak regions. A Na and annihilation doublet may be located among the peak regions. A predetermined energy level may be applied to one of the peaks in the doublet and a location of a hydrogen peak may be predicted based on the location of at least one of the peaks of the doublet. Control systems for calibrating spectra are also disclosed.

Recent advances in the modeling of plasmas with the Particle-In-Cell methods

NASA Astrophysics Data System (ADS)

Vay, Jean-Luc; Lehe, Remi; Vincenti, Henri; Godfrey, Brendan; Lee, Patrick; Haber, Irv

2015-11-01

The Particle-In-Cell (PIC) approach is the method of choice for self-consistent simulations of plasmas from first principles. The fundamentals of the PIC method were established decades ago but improvements or variations are continuously being proposed. We report on several recent advances in PIC related algorithms, including: (a) detailed analysis of the numerical Cherenkov instability and its remediation, (b) analytic pseudo-spectral electromagnetic solvers in Cartesian and cylindrical (with azimuthal modes decomposition) geometries, (c) arbitrary-order finite-difference and generalized pseudo-spectral Maxwell solvers, (d) novel analysis of Maxwell's solvers' stencil variation and truncation, in application to domain decomposition strategies and implementation of Perfectly Matched Layers in high-order and pseudo-spectral solvers. Work supported by US-DOE Contracts DE-AC02-05CH11231 and the US-DOE SciDAC program ComPASS. Used resources of NERSC, supported by US-DOE Contract DE-AC02-05CH11231.

A novel spectral resolution and simultaneous determination of multicomponent mixture of Vitamins B1, B6, B12, Benfotiamine and Diclofenac in tablets and capsules by derivative and MCR-ALS.

PubMed

Hegazy, Maha A; Abdelwahab, Nada S; Fayed, Ahmed S

2015-04-05

A novel method was developed for spectral resolution and further determination of five-component mixture including Vitamin B complex (B1, B6, B12 and Benfotiamine) along with the commonly co-formulated Diclofenac. The method is simple, sensitive, precise and could efficiently determine the five components by a complementary application of two different techniques. The first is univariate second derivative method that was successfully applied for determination of Vitamin B12. The second is Multivariate Curve Resolution using the Alternating Least Squares method (MCR-ALS) by which an efficient resolution and quantitation of the quaternary spectrally overlapped Vitamin B1, Vitamin B6, Benfotiamine and Diclofenac sodium were achieved. The effect of different constraints was studied and the correlation between the true spectra and the estimated spectral profiles were found to be 0.9998, 0.9983, 0.9993 and 0.9933 for B1, B6, Benfotiamine and Diclofenac, respectively. All components were successfully determined in tablets and capsules and the results were compared to HPLC methods and they were found to be statistically non-significant. Copyright © 2015 Elsevier B.V. All rights reserved.

A-TEEMTM, a new molecular fingerprinting technique: simultaneous absorbance-transmission and fluorescence excitation-emission matrix method

NASA Astrophysics Data System (ADS)

Quatela, Alessia; Gilmore, Adam M.; Steege Gall, Karen E.; Sandros, Marinella; Csatorday, Karoly; Siemiarczuk, Alex; (Ben Yang, Boqian; Camenen, Loïc

2018-04-01

We investigate the new simultaneous absorbance-transmission and fluorescence excitation-emission matrix method for rapid and effective characterization of the varying components from a mixture. The absorbance-transmission and fluorescence excitation-emission matrix method uniquely facilitates correction of fluorescence inner-filter effects to yield quantitative fluorescence spectral information that is largely independent of component concentration. This is significant because it allows one to effectively monitor quantitative component changes using multivariate methods and to generate and evaluate spectral libraries. We present the use of this novel instrument in different fields: i.e. tracking changes in complex mixtures including natural water, wine as well as monitoring stability and aggregation of hormones for biotherapeutics.

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

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.

Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain signals.

PubMed

Demanuele, Charmaine; James, Christopher J; Sonuga-Barke, Edmund Js

2007-12-10

It has been acknowledged that the frequency spectrum of measured electromagnetic (EM) brain signals shows a decrease in power with increasing frequency. This spectral behaviour may lead to difficulty in distinguishing event-related peaks from ongoing brain activity in the electro- and magnetoencephalographic (EEG and MEG) signal spectra. This can become an issue especially in the analysis of low frequency oscillations (LFOs) - below 0.5 Hz - which are currently being observed in signal recordings linked with specific pathologies such as epileptic seizures or attention deficit hyperactivity disorder (ADHD), in sleep studies, etc. In this work we propose a simple method that can be used to compensate for this 1/f trend hence achieving spectral normalisation. This method involves filtering the raw measured EM signal through a differentiator prior to further data analysis. Applying the proposed method to various exemplary datasets including very low frequency EEG recordings, epileptic seizure recordings, MEG data and Evoked Response data showed that this compensating procedure provides a flat spectral base onto which event related peaks can be clearly observed. Findings suggest that the proposed filter is a useful tool for the analysis of physiological data especially in revealing very low frequency peaks which may otherwise be obscured by the 1/f spectral activity inherent in EEG/MEG recordings.

Super-resolution reconstruction of hyperspectral images.

PubMed

Akgun, Toygar; Altunbasak, Yucel; Mersereau, Russell M

2005-11-01

Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super-resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions.

Legendre spectral-collocation method for solving some types of fractional optimal control problems

PubMed Central

Sweilam, Nasser H.; Al-Ajami, Tamer M.

2014-01-01

In this paper, the Legendre spectral-collocation method was applied to obtain approximate solutions for some types of fractional optimal control problems (FOCPs). The fractional derivative was described in the Caputo sense. Two different approaches were presented, in the first approach, necessary optimality conditions in terms of the associated Hamiltonian were approximated. In the second approach, the state equation was discretized first using the trapezoidal rule for the numerical integration followed by the Rayleigh–Ritz method to evaluate both the state and control variables. Illustrative examples were included to demonstrate the validity and applicability of the proposed techniques. PMID:26257937

A fast conservative spectral solver for the nonlinear Boltzmann collision operator

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

Gamba, Irene M.; Haack, Jeffrey R.; Hu, Jingwei

2014-12-09

We present a conservative spectral method for the fully nonlinear Boltzmann collision operator based on the weighted convolution structure in Fourier space developed by Gamba and Tharkabhushnanam. This method can simulate a broad class of collisions, including both elastic and inelastic collisions as well as angularly dependent cross sections in which grazing collisions play a major role. The extension presented in this paper consists of factorizing the convolution weight on quadrature points by exploiting the symmetric nature of the particle interaction law, which reduces the computational cost and memory requirements of the method to O(M{sup 2}N{sup 4}logN) from the O(N{supmore » 6}) complexity of the original spectral method, where N is the number of velocity grid points in each velocity dimension and M is the number of quadrature points in the factorization, which can be taken to be much smaller than N. We present preliminary numerical results.« less

Ocean Color Measurements from Landsat-8 OLI using SeaDAS

NASA Technical Reports Server (NTRS)

Franz, Bryan Alden; Bailey, Sean W.; Kuring, Norman; Werdell, P. Jeremy

2014-01-01

The Operational Land Imager (OLI) is a multi-spectral radiometer hosted on the recently launched Landsat-8 satellite. OLI includes a suite of relatively narrow spectral bands at 30-meter spatial resolution in the visible to shortwave infrared that make it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in SeaDAS, which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of satellite-based multi-spectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote-sensing reflectance (Rrs; sr exp 1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents such as the concentration of the phytoplankton pigment chlorophyll a.

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.

Extinction spectra of suspensions of microspheres: determination of the spectral refractive index and particle size distribution with nanometer accuracy.

PubMed

Gienger, Jonas; Bär, Markus; Neukammer, Jörg

2018-01-10

A method is presented to infer simultaneously the wavelength-dependent real refractive index (RI) of the material of microspheres and their size distribution from extinction measurements of particle suspensions. To derive the averaged spectral optical extinction cross section of the microspheres from such ensemble measurements, we determined the particle concentration by flow cytometry to an accuracy of typically 2% and adjusted the particle concentration to ensure that perturbations due to multiple scattering are negligible. For analysis of the extinction spectra, we employ Mie theory, a series-expansion representation of the refractive index and nonlinear numerical optimization. In contrast to other approaches, our method offers the advantage to simultaneously determine size, size distribution, and spectral refractive index of ensembles of microparticles including uncertainty estimation.

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.

Rapid screening of guar gum using portable Raman spectral identification methods.

PubMed

Srivastava, Hirsch K; Wolfgang, Steven; Rodriguez, Jason D

2016-01-25

Guar gum is a well-known inactive ingredient (excipient) used in a variety of oral pharmaceutical dosage forms as a thickener and stabilizer of suspensions and as a binder of powders. It is also widely used as a food ingredient in which case alternatives with similar properties, including chemically similar gums, are readily available. Recent supply shortages and price fluctuations have caused guar gum to come under increasing scrutiny for possible adulteration by substitution of cheaper alternatives. One way that the U.S. FDA is attempting to screen pharmaceutical ingredients at risk for adulteration or substitution is through field-deployable spectroscopic screening. Here we report a comprehensive approach to evaluate two field-deployable Raman methods--spectral correlation and principal component analysis--to differentiate guar gum from other gums. We report a comparison of the sensitivity of the spectroscopic screening methods with current compendial identification tests. The ability of the spectroscopic methods to perform unambiguous identification of guar gum compared to other gums makes them an enhanced surveillance alternative to the current compendial identification tests, which are largely subjective in nature. Our findings indicate that Raman spectral identification methods perform better than compendial identification methods and are able to distinguish guar gum from other gums with 100% accuracy for samples tested by spectral correlation and principal component analysis. Published by Elsevier B.V.

Applying aerial digital photography as a spectral remote sensing technique for macrophytic cover assessment in small rural streams

NASA Astrophysics Data System (ADS)

Anker, Y.; Hershkovitz, Y.; Gasith, A.; Ben-Dor, E.

2011-12-01

Although remote sensing of fluvial ecosystems is well developed, the tradeoff between spectral and spatial resolutions prevents its application in small streams (<3m width). In the current study, a remote sensing approach for monitoring and research of small ecosystem was developed. The method is based on differentiation between two indicative vegetation species out of the ecosystem flora. Since when studied, the channel was covered mostly by a filamentous green alga (Cladophora glomerata) and watercress (Nasturtium officinale), these species were chosen as indicative; nonetheless, common reed (Phragmites australis) was also classified in order to exclude it from the stream ROI. The procedure included: A. For both section and habitat scales classifications, acquisition of aerial digital RGB datasets. B. For section scale classification, hyperspectral (HSR) dataset acquisition. C. For calibration, HSR reflectance measurements of specific ground targets, in close proximity to each dataset acquisition swath. D. For habitat scale classification, manual, in-stream flora grid transects classification. The digital RGB datasets were converted to reflectance units by spectral calibration against colored reference plates. These red, green, blue, white, and black EVA foam reference plates were measured by an ASD field spectrometer and each was given a spectral value. Each spectral value was later applied to the spectral calibration and radiometric correction of spectral RGB (SRGB) cube. Spectral calibration of the HSR dataset was done using the empirical line method, based on reference values of progressive grey scale targets. Differentiation between the vegetation species was done by supervised classification both for the HSR and for the SRGB datasets. This procedure was done using the Spectral Angle Mapper function with the spectral pattern of each vegetation species as a spectral end member. Comparison between the two remote sensing techniques and between the SRGB classification and the in-situ transects indicates that: A. Stream vegetation classification resolution is about 4 cm by the SRGB method compared to about 1 m by HSR. Moreover, this resolution is also higher than of the manual grid transect classification. B. The SRGB method is by far the most cost-efficient. The combination of spectral information (rather than the cognitive color) and high spatial resolution of aerial photography provides noise filtration and better sub-water detection capabilities than the HSR technique. C. Only the SRGB method applies for habitat and section scales; hence, its application together with in-situ grid transects for validation, may be optimal for use in similar scenarios.
The HSR dataset was first degraded to 17 bands with the same spectral range as the RGB dataset and also to a dataset with 3 equivalent bands

A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation

NASA Astrophysics Data System (ADS)

Zhou, Xiran; Liu, Jun; Liu, Shuguang; Cao, Lei; Zhou, Qiming; Huang, Huawen

2014-02-01

High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity-hue-saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods.

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.

A review of spectral methods

NASA Technical Reports Server (NTRS)

Lustman, L.

1984-01-01

An outline for spectral methods for partial differential equations is presented. The basic spectral algorithm is defined, collocation are emphasized and the main advantage of the method, the infinite order of accuracy in problems with smooth solutions are discussed. Examples of theoretical numerical analysis of spectral calculations are presented. An application of spectral methods to transonic flow is presented. The full potential transonic equation is among the best understood among nonlinear equations.

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

A hyperspectral imaging system for the evaluation of the human iris spectral reflectance

NASA Astrophysics Data System (ADS)

Di Cecilia, Luca; Marazzi, Francesco; Rovati, Luigi

2017-02-01

According to previous studies, the measurement of the human iris pigmentation can be exploited to detect certain eye pathological conditions in their early stage. In this paper, we propose an instrument and a method to perform hyperspectral quantitative measurements of the iris spectral reflectance. The system is based on a simple imaging setup, which includes a monochrome camera mounted on a standard ophthalmic microscope movement controller, a monochromator, and a flashing LED-based slit lamp. To assure quantitative measurements, the system is properly calibrated against a NIST reflectance standard. Iris reflectance images can be obtained in the spectral range 495-795 nm with a resolution of 25 nm. Each image consists of 1280 x 1024 pixels having a spatial resolution of 18 μm. Reflectance spectra can be calculated both from discrete areas of the iris and as the average of the whole iris surface. Preliminary results suggest that hyperspectral imaging of the iris can provide much more morphological and spectral information with respect to conventional qualitative colorimetric methods.

A new mathematical formulation of the line-by-line method in case of weak line overlapping

NASA Technical Reports Server (NTRS)

Ishov, Alexander G.; Krymova, Natalie V.

1994-01-01

A rigorous mathematical proof is presented for multiline representation on the equivalent width of a molecular band which consists in the general case of n overlapping spectral lines. The multiline representation includes a principal term and terms of minor significance. The principal term is the equivalent width of the molecular band consisting of the same n nonoverlapping spectral lines. The terms of minor significance take into consideration the overlapping of two, three and more spectral lines. They are small in case of the weak overlapping of spectral lines in the molecular band. The multiline representation can be easily generalized for optically inhomogeneous gas media and holds true for combinations of molecular bands. If the band lines overlap weakly the standard formulation of line-by-line method becomes too labor-consuming. In this case the multiline representation permits line-by-line calculations to be performed more effectively. Other useful properties of the multiline representation are pointed out.

Improvements to an earth observing statistical performance model with applications to LWIR spectral variability

NASA Astrophysics Data System (ADS)

Zhao, Runchen; Ientilucci, Emmett J.

2017-05-01

Hyperspectral remote sensing systems provide spectral data composed of hundreds of narrow spectral bands. Spectral remote sensing systems can be used to identify targets, for example, without physical interaction. Often it is of interested to characterize the spectral variability of targets or objects. The purpose of this paper is to identify and characterize the LWIR spectral variability of targets based on an improved earth observing statistical performance model, known as the Forecasting and Analysis of Spectroradiometric System Performance (FASSP) model. FASSP contains three basic modules including a scene model, sensor model and a processing model. Instead of using mean surface reflectance only as input to the model, FASSP transfers user defined statistical characteristics of a scene through the image chain (i.e., from source to sensor). The radiative transfer model, MODTRAN, is used to simulate the radiative transfer based on user defined atmospheric parameters. To retrieve class emissivity and temperature statistics, or temperature / emissivity separation (TES), a LWIR atmospheric compensation method is necessary. The FASSP model has a method to transform statistics in the visible (ie., ELM) but currently does not have LWIR TES algorithm in place. This paper addresses the implementation of such a TES algorithm and its associated transformation of statistics.

Spectral methods and their implementation to solution of aerodynamic and fluid mechanic problems

NASA Technical Reports Server (NTRS)

Streett, C. L.

1987-01-01

Fundamental concepts underlying spectral collocation methods, especially pertaining to their use in the solution of partial differential equations, are outlined. Theoretical accuracy results are reviewed and compared with results from test problems. A number of practical aspects of the construction and use of spectral methods are detailed, along with several solution schemes which have found utility in applications of spectral methods to practical problems. Results from a few of the successful applications of spectral methods to problems of aerodynamic and fluid mechanic interest are then outlined, followed by a discussion of the problem areas in spectral methods and the current research under way to overcome these difficulties.

A facile synthesis and carbon-13 nuclear magnetic resonance spectral properties of 7-ketocholesteryl benzoate.

PubMed

Parish, E J; Wei, T Y; Livant, P

1987-10-01

This paper presents a modified method of the selective allylic oxidation of cholesteryl benzoate. Pyridinium chlorochromate, in refluxing benzene, has been found to be an effective and convenient reagent for the efficient oxidation of cholesteryl benzoate to 7-ketocholesteryl benzoate in high yield. Also included herein are the carbon-13 nuclear magnetic resonance spectral properties of 7-ketocholesteryl benzoate and cholesteryl benzoate.

Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library.

PubMed

Lachaud, Laurence; Fernández-Arévalo, Anna; Normand, Anne-Cécile; Lami, Patrick; Nabet, Cécile; Donnadieu, Jean Luc; Piarroux, Martine; Djenad, Farid; Cassagne, Carole; Ravel, Christophe; Tebar, Silvia; Llovet, Teresa; Blanchet, Denis; Demar, Magalie; Harrat, Zoubir; Aoun, Karim; Bastien, Patrick; Muñoz, Carmen; Gállego, Montserrat; Piarroux, Renaud

2017-10-01

Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-based application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani , L. guyanensis , and L. braziliensis complexes was observed, as previously reported for other techniques. The tested application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers. Copyright © 2017 American Society for Microbiology.

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.

Individual spectral densities and molecular motion in polycrystalline hexamethylbenzene-d18

NASA Astrophysics Data System (ADS)

Hoatson, Gina L.; Vold, Robert L.; Tse, Tak Y.

1994-04-01

Methods are described for obtaining the orientation dependence of individual motional spectral densities, J1(ω0) and J2(2ω0), from deuterium spin relaxation experiments on polycrystalline materials. Spectral density measurements provide detailed information in a motional regime too fast to be studied by the two-dimensional (2D) exchange method. Their potential as a source of detailed kinetic and geometric information is illustrated for hexamethylbenzene-d18 (HMB). The relaxation behavior of HMB cannot be explained exclusively by six-site jumps around the C6v axis. Agreement between the experimentally determined spectral densities and simulations is improved if the methyl rotation is explicitly included. At ambient temperature the experimental data are best fitted with the simultaneous jump rates, k6=3.85×108 s-1 and k3=5.0×1011 s-1. This is significantly different from the rate determined using a simple six-site jump model, k6=3.9×109 s-1. Geometric distortions of the methyl rotation axes can account for the observed motionally averaged electric field gradient tensor. When these distortions are included in analysis of the spectral density data, there is a small, but significant, improvement in the fit. k3 is unchanged and the best fit k6 is reduced to 2.2×108 s-1, with distortions out of plane by δ=2.5° and in plane ɛ=ɛ'=1.202.

Separating Atmospheric and Surface Contributions in Hyperspectral Imager for the Coastal Ocean (HICO) Scenes using Informed Non-Negative Matrix Factorization

NASA Astrophysics Data System (ADS)

Wright, L.; Coddington, O.; Pilewskie, P.

2016-12-01

Hyperspectral instruments are a growing class of Earth observing sensors designed to improve remote sensing capabilities beyond discrete multi-band sensors by providing tens to hundreds of continuous spectral channels. Improved spectral resolution, range and radiometric accuracy allow the collection of large amounts of spectral data, facilitating thorough characterization of both atmospheric and surface properties. These new instruments require novel approaches for processing imagery and separating surface and atmospheric signals. One approach is numerical source separation, which allows the determination of the underlying physical causes of observed signals. Improved source separation will enable hyperspectral imagery to better address key science questions relevant to climate change, including land-use changes, trends in clouds and atmospheric water vapor, and aerosol characteristics. We developed an Informed Non-negative Matrix Factorization (INMF) method for separating atmospheric and surface sources. INMF offers marked benefits over other commonly employed techniques including non-negativity, which avoids physically impossible results; and adaptability, which tailors the method to hyperspectral source separation. The INMF algorithm is adapted to separate contributions from physically distinct sources using constraints on spectral and spatial variability, and library spectra to improve the initial guess. We also explore methods to produce an initial guess of the spatial separation patterns. Using this INMF algorithm we decompose hyperspectral imagery from the NASA Hyperspectral Imager for the Coastal Ocean (HICO) with a focus on separating surface and atmospheric signal contributions. HICO's coastal ocean focus provides a dataset with a wide range of atmospheric conditions, including high and low aerosol optical thickness and cloud cover, with only minor contributions from the ocean surfaces in order to isolate the contributions of the multiple atmospheric sources.

Laser-induced fluorescence fiber optic probe measurement of oil dilution by fuel

DOEpatents

Parks, II, James E [Knoxville, TN; Partridge, Jr., William P [Oak Ridge, TN

2010-11-23

Apparatus for detecting fuel in oil includes an excitation light source in optical communication with an oil sample for exposing the oil sample to excitation light in order to excite the oil sample from a non-excited state to an excited state and a spectrally selective device in optical communication with the oil sample for detecting light emitted from the oil sample as the oil sample returns from the excited state to a non-excited state to produce spectral indicia that can be analyzed to determine the presence of fuel in the oil sample. A method of detecting fuel in oil includes the steps of exposing a oil sample to excitation light in order to excite the oil sample from a non-excited state to an excited state, as the oil sample returns from the excited state to a non-excited state, detecting light emitted from the oil sample to produce spectral indicia; and analyzing the spectral indicia to determine the presence of fuel in the oil sample.

An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

NASA Astrophysics Data System (ADS)

Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

2017-09-01

Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

A method for predicting the noise levels of coannular jets with inverted velocity profiles

NASA Technical Reports Server (NTRS)

Russell, J. W.

1979-01-01

A coannular jet was equated with a single stream equivalent jet with the same mass flow, energy, and thrust. The acoustic characteristics of the coannular jet were then related to the acoustic characteristics of the single jet. Forward flight effects were included by incorporating a forward exponent, a Doppler amplification factor, and a Strouhal frequency shift. Model test data, including 48 static cases and 22 wind tunnel cases, were used to evaluate the prediction method. For the static cases and the low forward velocity wind tunnel cases, the spectral mean square pressure correlation coefficients were generally greater than 90 percent, and the spectral sound pressure level standard deviation were generally less than 3 decibels. The correlation coefficient and the standard deviation were not affected by changes in equivalent jet velocity. Limitations of the prediction method are also presented.

Spectral CT of the extremities with a silicon strip photon counting detector

NASA Astrophysics Data System (ADS)

Sisniega, A.; Zbijewski, W.; Stayman, J. W.; Xu, J.; Taguchi, K.; Siewerdsen, J. H.

2015-03-01

Purpose: Photon counting x-ray detectors (PCXDs) are an important emerging technology for spectral imaging and material differentiation with numerous potential applications in diagnostic imaging. We report development of a Si-strip PCXD system originally developed for mammography with potential application to spectral CT of musculoskeletal extremities, including challenges associated with sparse sampling, spectral calibration, and optimization for higher energy x-ray beams. Methods: A bench-top CT system was developed incorporating a Si-strip PCXD, fixed anode x-ray source, and rotational and translational motions to execute complex acquisition trajectories. Trajectories involving rotation and translation combined with iterative reconstruction were investigated, including single and multiple axial scans and longitudinal helical scans. The system was calibrated to provide accurate spectral separation in dual-energy three-material decomposition of soft-tissue, bone, and iodine. Image quality and decomposition accuracy were assessed in experiments using a phantom with pairs of bone and iodine inserts (3, 5, 15 and 20 mm) and an anthropomorphic wrist. Results: The designed trajectories improved the sampling distribution from 56% minimum sampling of voxels to 75%. Use of iterative reconstruction (viz., penalized likelihood with edge preserving regularization) in combination with such trajectories resulted in a very low level of artifacts in images of the wrist. For large bone or iodine inserts (>5 mm diameter), the error in the estimated material concentration was <16% for (50 mg/mL) bone and <8% for (5 mg/mL) iodine with strong regularization. For smaller inserts, errors of 20-40% were observed and motivate improved methods for spectral calibration and optimization of the edge-preserving regularizer. Conclusion: Use of PCXDs for three-material decomposition in joint imaging proved feasible through a combination of rotation-translation acquisition trajectories and iterative reconstruction with optimized regularization.

Spectral characterization and calibration of AOTF spectrometers and hyper-spectral imaging system

NASA Astrophysics Data System (ADS)

Katrašnik, Jaka; Pernuš, Franjo; Likar, Boštjan

2010-02-01

The goal of this article is to present a novel method for spectral characterization and calibration of spectrometers and hyper-spectral imaging systems based on non-collinear acousto-optical tunable filters. The method characterizes the spectral tuning curve (frequency-wavelength characteristic) of the AOTF (Acousto-Optic Tunable Filter) filter by matching the acquired and modeled spectra of the HgAr calibration lamp, which emits line spectrum that can be well modeled via AOTF transfer function. In this way, not only tuning curve characterization and corresponding spectral calibration but also spectral resolution assessment is performed. The obtained results indicated that the proposed method is efficient, accurate and feasible for routine calibration of AOTF spectrometers and hyper-spectral imaging systems and thereby a highly competitive alternative to the existing calibration methods.

Using hyperspectral imaging technology to identify diseased tomato leaves

NASA Astrophysics Data System (ADS)

Li, Cuiling; Wang, Xiu; Zhao, Xueguan; Meng, Zhijun; Zou, Wei

2016-11-01

In the process of tomato plants growth, due to the effect of plants genetic factors, poor environment factors, or disoperation of parasites, there will generate a series of unusual symptoms on tomato plants from physiology, organization structure and external form, as a result, they cannot grow normally, and further to influence the tomato yield and economic benefits. Hyperspectral image usually has high spectral resolution, not only contains spectral information, but also contains the image information, so this study adopted hyperspectral imaging technology to identify diseased tomato leaves, and developed a simple hyperspectral imaging system, including a halogen lamp light source unit, a hyperspectral image acquisition unit and a data processing unit. Spectrometer detection wavelength ranged from 400nm to 1000nm. After hyperspectral images of tomato leaves being captured, it was needed to calibrate hyperspectral images. This research used spectrum angle matching method and spectral red edge parameters discriminant method respectively to identify diseased tomato leaves. Using spectral red edge parameters discriminant method produced higher recognition accuracy, the accuracy was higher than 90%. Research results have shown that using hyperspectral imaging technology to identify diseased tomato leaves is feasible, and provides the discriminant basis for subsequent disease control of tomato plants.

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.

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.

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

PubMed

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can reliably be used in the low SNR data set (set B) compared to the high SNR data set (set A). Despite the fact that no definitive threshold could be found, this method may help to determine the cutoff for the number of principal components used in discriminant analysis. Future analysis of a selection of spectral databases using this technique will allow optimum thresholds to be selected for different applications and spectral data quality levels.

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.

[Variable selection methods combined with local linear embedding theory used for optimization of near infrared spectral quantitative models].

PubMed

Hao, Yong; Sun, Xu-Dong; Yang, Qiang

2012-12-01

Variables selection strategy combined with local linear embedding (LLE) was introduced for the analysis of complex samples by using near infrared spectroscopy (NIRS). Three methods include Monte Carlo uninformation variable elimination (MCUVE), successive projections algorithm (SPA) and MCUVE connected with SPA were used for eliminating redundancy spectral variables. Partial least squares regression (PLSR) and LLE-PLSR were used for modeling complex samples. The results shown that MCUVE can both extract effective informative variables and improve the precision of models. Compared with PLSR models, LLE-PLSR models can achieve more accurate analysis results. MCUVE combined with LLE-PLSR is an effective modeling method for NIRS quantitative analysis.

Simultaneous separation by reversed-phase high-performance liquid chromatography and mass spectral identification of anthocyanins and flavonols in Shiraz grape skin.

PubMed

Downey, Mark O; Rochfort, Simone

2008-08-01

A limitation of large-scale viticultural trials is the time and cost of comprehensive compositional analysis of the fruit by high-performance liquid chromatography (HPLC). In addition, separate methods have generally been required to identify and quantify different classes of metabolites. To address these shortcomings a reversed-phase HPLC method was developed to simultaneously separate the anthocyanins and flavonols present in grape skins. The method employs a methanol and water gradient acidified with 10% formic acid with a run-time of 48 min including re-equilibration. Identity of anthocyanins and flavonols in Shiraz (Vitis vinifera L.) skin was confirmed by mass spectral analysis.

Medipix-based Spectral Micro-CT.

PubMed

Yu, Hengyong; Xu, Qiong; He, Peng; Bennett, James; Amir, Raja; Dobbs, Bruce; Mou, Xuanqin; Wei, Biao; Butler, Anthony; Butler, Phillip; Wang, Ge

2012-12-01

Since Hounsfield's Nobel Prize winning breakthrough decades ago, X-ray CT has been widely applied in the clinical and preclinical applications - producing a huge number of tomographic gray-scale images. However, these images are often insufficient to distinguish crucial differences needed for diagnosis. They have poor soft tissue contrast due to inherent photon-count issues, involving high radiation dose. By physics, the X-ray spectrum is polychromatic, and it is now feasible to obtain multi-energy, spectral, or true-color, CT images. Such spectral images promise powerful new diagnostic information. The emerging Medipix technology promises energy-sensitive, high-resolution, accurate and rapid X-ray detection. In this paper, we will review the recent progress of Medipix-based spectral micro-CT with the emphasis on the results obtained by our team. It includes the state- of-the-art Medipix detector, the system and method of a commercial MARS (Medipix All Resolution System) spectral micro-CT, and the design and color diffusion of a hybrid spectral micro-CT.

The Python Spectral Analysis Tool (PySAT): A Powerful, Flexible, Preprocessing and Machine Learning Library and Interface

NASA Astrophysics Data System (ADS)

Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T. G.; Morris, R. V.; Laura, J.; Gaddis, L. R.

2017-12-01

Machine learning is a powerful but underutilized approach that can enable planetary scientists to derive meaningful results from the rapidly-growing quantity of available spectral data. For example, regression methods such as Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO), can be used to determine chemical concentrations from ChemCam and SuperCam Laser-Induced Breakdown Spectroscopy (LIBS) data [1]. Many scientists are interested in testing different spectral data processing and machine learning methods, but few have the time or expertise to write their own software to do so. We are therefore developing a free open-source library of software called the Python Spectral Analysis Tool (PySAT) along with a flexible, user-friendly graphical interface to enable scientists to process and analyze point spectral data without requiring significant programming or machine-learning expertise. A related but separately-funded effort is working to develop a graphical interface for orbital data [2]. The PySAT point-spectra tool includes common preprocessing steps (e.g. interpolation, normalization, masking, continuum removal, dimensionality reduction), plotting capabilities, and capabilities to prepare data for machine learning such as creating stratified folds for cross validation, defining training and test sets, and applying calibration transfer so that data collected on different instruments or under different conditions can be used together. The tool leverages the scikit-learn library [3] to enable users to train and compare the results from a variety of multivariate regression methods. It also includes the ability to combine multiple "sub-models" into an overall model, a method that has been shown to improve results and is currently used for ChemCam data [4]. Although development of the PySAT point-spectra tool has focused primarily on the analysis of LIBS spectra, the relevant steps and methods are applicable to any spectral data. The tool is available at https://github.com/USGS-Astrogeology/PySAT_Point_Spectra_GUI. [1] Clegg, S.M., et al. (2017) Spectrochim Acta B. 129, 64-85. [2] Gaddis, L. et al. (2017) 3rd Planetary Data Workshop, #1986. [3] http://scikit-learn.org/ [4] Anderson, R.B., et al. (2017) Spectrochim. Acta B. 129, 49-57.

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution, appendix 2

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1988-01-01

This thesis reviews the technique established to clear channels in the Power Spectral Estimate by applying linear combinations of well known window functions to the autocorrelation function. The need for windowing the auto correlation function is due to the fact that the true auto correlation is not generally used to obtain the Power Spectral Estimate. When applied, the windows serve to reduce the effect that modifies the auto correlation by truncating the data and possibly the autocorrelation has on the Power Spectral Estimate. It has been shown in previous work that a single channel has been cleared, allowing for the detection of a small peak in the presence of a large peak in the Power Spectral Estimate. The utility of this method is dependent on the robustness of it on different input situations. We extend the analysis in this paper, to include clearing up to three channels. We examine the relative positions of the spikes to each other and also the effect of taking different percentages of lags of the auto correlation in the Power Spectral Estimate. This method could have application wherever the Power Spectrum is used. An example of this is beam forming for source location, where a small target can be located next to a large target. Other possibilities extend into seismic data processing. As the method becomes more automated other applications may present themselves.

An Expert System for Classifying Stars on the MK Spectral Classification System

NASA Astrophysics Data System (ADS)

Corbally, Christopher J.; Gray, R. O.

2013-01-01

We will describe an expert computer system designed to classify stellar spectra on the MK Spectral Classification system employing methods similar to those of humans who make direct comparison with the MK classification standards. Like an expert human classifier, MKCLASS first comes up with a rough spectral type, and then refines that type by direct comparison with MK standards drawn from a standards library using spectral criteria appropriate to the spectral class. Certain common spectral-type peculiarities can also be detected by the program. The program is also capable of identifying WD spectra and carbon stars and giving appropriate (but currently approximate) spectral types on the relevant systems. We will show comparisons between spectral types (including luminosity types) performed by MKCLASS and humans. The program currently is capable of competent classifications in the violet-green region, but plans are underway to extend the spectral criteria into the red and near-infrared regions. Two standard libraries with resolutions of 1.8 and 3.6Å are now available, but a higher-resolution standard library, using the new spectrograph on the Vatican Advanced Technology Telescope, is currently under preparation. Once that library is available, MKCLASS and the spectral libraries will be made available to the astronomical community.

Comparison of heaving buoy and oscillating flap wave energy converters

NASA Astrophysics Data System (ADS)

Abu Bakar, Mohd Aftar; Green, David A.; Metcalfe, Andrew V.; Najafian, G.

2013-04-01

Waves offer an attractive source of renewable energy, with relatively low environmental impact, for communities reasonably close to the sea. Two types of simple wave energy converters (WEC), the heaving buoy WEC and the oscillating flap WEC, are studied. Both WECs are considered as simple energy converters because they can be modelled, to a first approximation, as single degree of freedom linear dynamic systems. In this study, we estimate the response of both WECs to typical wave inputs; wave height for the buoy and corresponding wave surge for the flap, using spectral methods. A nonlinear model of the oscillating flap WEC that includes the drag force, modelled by the Morison equation is also considered. The response to a surge input is estimated by discrete time simulation (DTS), using central difference approximations to derivatives. This is compared with the response of the linear model obtained by DTS and also validated using the spectral method. Bendat's nonlinear system identification (BNLSI) technique was used to analyze the nonlinear dynamic system since the spectral analysis was only suitable for linear dynamic system. The effects of including the nonlinear term are quantified.

A novel and compact spectral imaging system based on two curved prisms

NASA Astrophysics Data System (ADS)

Nie, Yunfeng; Bin, Xiangli; Zhou, Jinsong; Li, Yang

2013-09-01

As a novel detection approach which simultaneously acquires two-dimensional visual picture and one-dimensional spectral information, spectral imaging offers promising applications on biomedical imaging, conservation and identification of artworks, surveillance of food safety, and so forth. A novel moderate-resolution spectral imaging system consisting of merely two optical elements is illustrated in this paper. It can realize the function of a relay imaging system as well as a 10nm spectral resolution spectroscopy. Compared to conventional prismatic imaging spectrometers, this design is compact and concise with only two special curved prisms by utilizing two reflective surfaces. In contrast to spectral imagers based on diffractive grating, the usage of compound-prism possesses characteristics of higher energy utilization and wider free spectral range. The seidel aberration theory and dispersive principle of this special prism are analyzed at first. According to the results, the optical system of this design is simulated, and the performance evaluation including spot diagram, MTF and distortion, is presented. In the end, considering the difficulty and particularity of manufacture and alignment, an available method for fabrication and measurement is proposed.

Mean centering of ratio spectra and concentration augmented classical least squares in a comparative approach for quantitation of spectrally overlapped bands of antihypertensives in formulations

NASA Astrophysics Data System (ADS)

Hegazy, Maha Abdel Monem; Fayez, Yasmin Mohammed

2015-04-01

Two different methods manipulating spectrophotometric data have been developed, validated and compared. One is capable of removing the signal of any interfering components at the selected wavelength of the component of interest (univariate). The other includes more variables and extracts maximum information to determine the component of interest in the presence of other components (multivariate). The applied methods are smart, simple, accurate, sensitive, precise and capable of determination of spectrally overlapped antihypertensives; hydrochlorothiazide (HCT), irbesartan (IRB) and candesartan (CAN). Mean centering of ratio spectra (MCR) and concentration residual augmented classical least-squares method (CRACLS) were developed and their efficiency was compared. CRACLS is a simple method that is capable of extracting the pure spectral profiles of each component in a mixture. Correlation was calculated between the estimated and pure spectra and was found to be 0.9998, 0.9987 and 0.9992 for HCT, IRB and CAN, respectively. The methods were successfully determined the three components in bulk powder, laboratory-prepared mixtures, and combined dosage forms. The results obtained were compared statistically with each other and to those of the official methods.

Extracting biomolecule collision cross sections from the high-resolution FT-ICR mass spectral linewidths.

PubMed

Jiang, Ting; Chen, Yu; Mao, Lu; Marshall, Alan G; Xu, Wei

2016-01-14

It is known that the ion collision cross section (CCS) may be calculated from the linewidth of a Fourier transform ion cyclotron resonance (FT-ICR) mass spectral peak at elevated pressure (e.g., ∼10(-6) Torr). However, the high mass resolution of FT-ICR is sacrificed in those experiments due to high buffer gas pressure. In this study, we describe a linewidth correction method to eliminate the windowing-induced peak broadening effect. Together with the energetic ion-neutral collision model previously developed by our group, this method enables the extraction of CCSs of biomolecules from high-resolution FT-ICR mass spectral linewidths, obtained at a typical operating buffer gas pressure of modern FT-ICR instruments (∼10(-10) Torr). CCS values of peptides including MRFA, angiotensin I, and bradykinin measured by the proposed method agree well with ion mobility measurements, and the unfolding of protein ions (ubiquitin) at higher charge states is also observed.

[Building Mass Spectrometry Spectral Libraries of Human Cancer Cell Lines].

PubMed

Faktor, J; Bouchal, P

Cancer research often focuses on protein quantification in model cancer cell lines and cancer tissues. SWATH (sequential windowed acquisition of all theoretical fragment ion spectra), the state of the art method, enables the quantification of all proteins included in spectral library. Spectral library contains fragmentation patterns of each detectable protein in a sample. Thorough spectral library preparation will improve quantitation of low abundant proteins which usually play an important role in cancer. Our research is focused on the optimization of spectral library preparation aimed at maximizing the number of identified proteins in MCF-7 breast cancer cell line. First, we optimized the sample preparation prior entering the mass spectrometer. We examined the effects of lysis buffer composition, peptide dissolution protocol and the material of sample vial on the number of proteins identified in spectral library. Next, we optimized mass spectrometry (MS) method for spectral library data acquisition. Our thorough optimized protocol for spectral library building enabled the identification of 1,653 proteins (FDR < 1%) in 1 µg of MCF-7 lysate. This work contributed to the enhancement of protein coverage in SWATH digital biobanks which enable quantification of arbitrary protein from physically unavailable samples. In future, high quality spectral libraries could play a key role in preparing of patient proteome digital fingerprints.Key words: biomarker - mass spectrometry - proteomics - digital biobanking - SWATH - protein quantificationThis work was supported by the project MEYS - NPS I - LO1413.The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.Submitted: 7. 5. 2016Accepted: 9. 6. 2016.

Reconstructing Spectral Scenes Using Statistical Estimation to Enhance Space Situational Awareness

DTIC Science & Technology

2006-12-01

simultane- ously spatially and spectrally deblur the images collected from ASIS. The algorithms are based on proven estimation theories and do not...collected with any system using a filtering technology known as Electronic Tunable Filters (ETFs). Previous methods to deblur spectral images collected...spectrally deblurring then the previously investigated methods. This algorithm expands on a method used for increasing the spectral resolution in gamma-ray

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.

Initial study of Schroedinger eigenmaps for spectral target detection

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.; Messinger, David W.

2016-08-01

Spectral target detection refers to the process of searching for a specific material with a known spectrum over a large area containing materials with different spectral signatures. Traditional target detection methods in hyperspectral imagery (HSI) require assuming the data fit some statistical or geometric models and based on the model, to estimate parameters for defining a hypothesis test, where one class (i.e., target class) is chosen over the other classes (i.e., background class). Nonlinear manifold learning methods such as Laplacian eigenmaps (LE) have extensively shown their potential use in HSI processing, specifically in classification or segmentation. Recently, Schroedinger eigenmaps (SE), which is built upon LE, has been introduced as a semisupervised classification method. In SE, the former Laplacian operator is replaced by the Schroedinger operator. The Schroedinger operator includes by definition, a potential term V that steers the transformation in certain directions improving the separability between classes. In this regard, we propose a methodology for target detection that is not based on the traditional schemes and that does not need the estimation of statistical or geometric parameters. This method is based on SE, where the potential term V is taken into consideration to include the prior knowledge about the target class and use it to steer the transformation in directions where the target location in the new space is known and the separability between target and background is augmented. An initial study of how SE can be used in a target detection scheme for HSI is shown here. In-scene pixel and spectral signature detection approaches are presented. The HSI data used comprise various target panels for testing simultaneous detection of multiple objects with different complexities.

Remote Sensing of Spectral Aerosol Properties: A Classroom Experience

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Pinker, Rachel T.

2006-01-01

Bridging the gap between current research and the classroom is a major challenge to today s instructor, especially in the sciences where progress happens quickly. NASA Goddard Space Flight Center and the University of Maryland teamed up in designing a graduate class project intended to provide a hands-on introduction to the physical basis for the retrieval of aerosol properties from state-of-the-art MODIS observations. Students learned to recognize spectral signatures of atmospheric aerosols and to perform spectral inversions. They became acquainted with the operational MODIS aerosol retrieval algorithm over oceans, and methods for its evaluation, including comparisons with groundbased AERONET sun-photometer data.

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

Spectrally controlled interferometry for measurements of flat and spherical optics

NASA Astrophysics Data System (ADS)

Salsbury, Chase; Olszak, Artur G.

2017-10-01

Conventional interferometry is widely used to measure spherical and at surfaces with nanometer level precision but is plagued by back reflections. We describe a new method of isolating the measurement surface by controlling spectral properties of the source (Spectrally Controlled Interferometry - SCI). Using spectral modulation of the interferometer's source enables formation of localized fringes where the optical path difference is non-zero. As a consequence it becomes possible to form white-light like fringes in common path interferometers, such as the Fizeau. The proposed setup does not require mechanical phase shifting, resulting in simpler instruments and the ability to upgrade existing interferometers. Furthermore, it allows absolute measurement of distance, including radius of curvature of lenses in a single setup with possibility of improving the throughput and removing some modes of failure.

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

Spectral Learning for Supervised Topic Models.

PubMed

Ren, Yong; Wang, Yining; Zhu, Jun

2018-03-01

Supervised topic models simultaneously model the latent topic structure of large collections of documents and a response variable associated with each document. Existing inference methods are based on variational approximation or Monte Carlo sampling, which often suffers from the local minimum defect. Spectral methods have been applied to learn unsupervised topic models, such as latent Dirichlet allocation (LDA), with provable guarantees. This paper investigates the possibility of applying spectral methods to recover the parameters of supervised LDA (sLDA). We first present a two-stage spectral method, which recovers the parameters of LDA followed by a power update method to recover the regression model parameters. Then, we further present a single-phase spectral algorithm to jointly recover the topic distribution matrix as well as the regression weights. Our spectral algorithms are provably correct and computationally efficient. We prove a sample complexity bound for each algorithm and subsequently derive a sufficient condition for the identifiability of sLDA. Thorough experiments on synthetic and real-world datasets verify the theory and demonstrate the practical effectiveness of the spectral algorithms. In fact, our results on a large-scale review rating dataset demonstrate that our single-phase spectral algorithm alone gets comparable or even better performance than state-of-the-art methods, while previous work on spectral methods has rarely reported such promising performance.

XMDS2: Fast, scalable simulation of coupled stochastic partial differential equations

NASA Astrophysics Data System (ADS)

Dennis, Graham R.; Hope, Joseph J.; Johnsson, Mattias T.

2013-01-01

XMDS2 is a cross-platform, GPL-licensed, open source package for numerically integrating initial value problems that range from a single ordinary differential equation up to systems of coupled stochastic partial differential equations. The equations are described in a high-level XML-based script, and the package generates low-level optionally parallelised C++ code for the efficient solution of those equations. It combines the advantages of high-level simulations, namely fast and low-error development, with the speed, portability and scalability of hand-written code. XMDS2 is a complete redesign of the XMDS package, and features support for a much wider problem space while also producing faster code. Program summaryProgram title: XMDS2 Catalogue identifier: AENK_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENK_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 2 No. of lines in distributed program, including test data, etc.: 872490 No. of bytes in distributed program, including test data, etc.: 45522370 Distribution format: tar.gz Programming language: Python and C++. Computer: Any computer with a Unix-like system, a C++ compiler and Python. Operating system: Any Unix-like system; developed under Mac OS X and GNU/Linux. RAM: Problem dependent (roughly 50 bytes per grid point) Classification: 4.3, 6.5. External routines: The external libraries required are problem-dependent. Uses FFTW3 Fourier transforms (used only for FFT-based spectral methods), dSFMT random number generation (used only for stochastic problems), MPI message-passing interface (used only for distributed problems), HDF5, GNU Scientific Library (used only for Bessel-based spectral methods) and a BLAS implementation (used only for non-FFT-based spectral methods). Nature of problem: General coupled initial-value stochastic partial differential equations. Solution method: Spectral method with method-of-lines integration Running time: Determined by the size of the problem

Single-Trial Normalization for Event-Related Spectral Decomposition Reduces Sensitivity to Noisy Trials

PubMed Central

Grandchamp, Romain; Delorme, Arnaud

2011-01-01

In electroencephalography, the classical event-related potential model often proves to be a limited method to study complex brain dynamics. For this reason, spectral techniques adapted from signal processing such as event-related spectral perturbation (ERSP) – and its variant event-related synchronization and event-related desynchronization – have been used over the past 20 years. They represent average spectral changes in response to a stimulus. These spectral methods do not have strong consensus for comparing pre- and post-stimulus activity. When computing ERSP, pre-stimulus baseline removal is usually performed after averaging the spectral estimate of multiple trials. Correcting the baseline of each single-trial prior to averaging spectral estimates is an alternative baseline correction method. However, we show that this method leads to positively skewed post-stimulus ERSP values. We eventually present new single-trial-based ERSP baseline correction methods that perform trial normalization or centering prior to applying classical baseline correction methods. We show that single-trial correction methods minimize the contribution of artifactual data trials with high-amplitude spectral estimates and are robust to outliers when performing statistical inference testing. We then characterize these methods in terms of their time–frequency responses and behavior compared to classical ERSP methods. PMID:21994498

Spectral methods for CFD

NASA Technical Reports Server (NTRS)

Zang, Thomas A.; Streett, Craig L.; Hussaini, M. Yousuff

1989-01-01

One of the objectives of these notes is to provide a basic introduction to spectral methods with a particular emphasis on applications to computational fluid dynamics. Another objective is to summarize some of the most important developments in spectral methods in the last two years. The fundamentals of spectral methods for simple problems will be covered in depth, and the essential elements of several fluid dynamical applications will be sketched.

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.

Sesquiterpenoids and phenolics from Taraxacum hondoense.

PubMed

Kisiel, Wanda; Michalska, Klaudia

2005-09-01

Eleven sesquiterpene lactones, including the new guaianolide 11beta-hydroxydeacetylmatricarin-8-O-beta-glucopyranoside, along with four known phenolic glucosides were isolated from Taraxacum hondoense. The compounds were characterized by spectral methods.

[Extracting black soil border in Heilongjiang province based on spectral angle match method].

PubMed

Zhang, Xin-Le; Zhang, Shu-Wen; Li, Ying; Liu, Huan-Jun

2009-04-01

As soils are generally covered by vegetation most time of a year, the spectral reflectance collected by remote sensing technique is from the mixture of soil and vegetation, so the classification precision based on remote sensing (RS) technique is unsatisfied. Under RS and geographic information systems (GIS) environment and with the help of buffer and overlay analysis methods, land use and soil maps were used to derive regions of interest (ROI) for RS supervised classification, which plus MODIS reflectance products were chosen to extract black soil border, with methods including spectral single match. The results showed that the black soil border in Heilongjiang province can be extracted with soil remote sensing method based on MODIS reflectance products, especially in the north part of black soil zone; the classification precision of spectral angel mapping method is the highest, but the classifying accuracy of other soils can not meet the need, because of vegetation covering and similar spectral characteristics; even for the same soil, black soil, the classifying accuracy has obvious spatial heterogeneity, in the north part of black soil zone in Heilongjiang province it is higher than in the south, which is because of spectral differences; as soil uncovering period in Northeastern China is relatively longer, high temporal resolution make MODIS images get the advantage over soil remote sensing classification; with the help of GIS, extracting ROIs by making the best of auxiliary data can improve the precision of soil classification; with the help of auxiliary information, such as topography and climate, the classification accuracy was enhanced significantly. As there are five main factors determining soil classes, much data of different types, such as DEM, terrain factors, climate (temperature, precipitation, etc.), parent material, vegetation map, and remote sensing images, were introduced to classify soils, so how to choose some of the data and quantify the weights of different data layers needs further study.

STATCONT: A statistical continuum level determination method for line-rich sources

NASA Astrophysics Data System (ADS)

Sánchez-Monge, Á.; Schilke, P.; Ginsburg, A.; Cesaroni, R.; Schmiedeke, A.

2018-01-01

STATCONT is a python-based tool designed to determine the continuum emission level in spectral data, in particular for sources with a line-rich spectrum. The tool inspects the intensity distribution of a given spectrum and automatically determines the continuum level by using different statistical approaches. The different methods included in STATCONT are tested against synthetic data. We conclude that the sigma-clipping algorithm provides the most accurate continuum level determination, together with information on the uncertainty in its determination. This uncertainty can be used to correct the final continuum emission level, resulting in the here called `corrected sigma-clipping method' or c-SCM. The c-SCM has been tested against more than 750 different synthetic spectra reproducing typical conditions found towards astronomical sources. The continuum level is determined with a discrepancy of less than 1% in 50% of the cases, and less than 5% in 90% of the cases, provided at least 10% of the channels are line free. The main products of STATCONT are the continuum emission level, together with a conservative value of its uncertainty, and datacubes containing only spectral line emission, i.e., continuum-subtracted datacubes. STATCONT also includes the option to estimate the spectral index, when different files covering different frequency ranges are provided.

Near-infrared spectral methods for noninvasively measuring blood glucose

NASA Astrophysics Data System (ADS)

Fei, Sun; Kong, Deyi; Mei, Tao; Tao, Yongchun

2004-05-01

Determination of blood glucose concentrations in diabetic patients is a frequently occurring procedure and an important tool for diabetes management. Use of noninvasive detection techniques can relieve patients from the pain of frequent finger pokes and avoid the infection of disease via blood. This thesis discusses current research and analyzes the advantages and shortages of different measurement methods, including: optical methods (Transmission, Polarimetry and scattering), then, we give emphasis to analyze the technology of near-infrared (NIR) spectra. NIR spectral range 700 nm ~2300 nm was used because of its good transparency for biological tissue and presence of glucose absorption band. In this work, we present an outline of noninvasive blood glucose measurement. A near-infrared light beam is passed through the finger, and the spectral components of the emergent beam are measured using spectroscopic techniques. The device includes light sources having the wavelengths of 600 nm - 1800 nm to illuminate the tissue. Receptors associated with the light sources for receiving light and generating a transmission signal representing the light transmitted are also provided. Once a transmission signal is received by receptors, and the high and low values from each of the signals are stored in the device. The averaged values are then analyzed to determine the glucose concentration, which is displayed on the device.

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.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

Fiberoptic probe and system for spectral measurements

DOEpatents

Dai, Sheng; Young, Jack P.

1998-01-01

A fused fiberoptic probe, a system, method and embodiments thereof for conducting spectral measurements are disclosed. The fused fiberoptic probe comprises a probe tip having a specific geometrical configuration, an exciting optical fiber and at least one collection optical fiber fused within a housing, preferrably silica. The specific geometrical configurations in which the probe tip can be shaped include a slanted probe tip with an angle greater than 0.degree., an inverted cone-shaped probe tip, and a lens head.

Constrained signal reconstruction from wavelet transform coefficients

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

Brislawn, C.M.

1991-12-31

A new method is introduced for reconstructing a signal from an incomplete sampling of its Discrete Wavelet Transform (DWT). The algorithm yields a minimum-norm estimate satisfying a priori upper and lower bounds on the signal. The method is based on a finite-dimensional representation theory for minimum-norm estimates of bounded signals developed by R.E. Cole. Cole`s work has its origins in earlier techniques of maximum-entropy spectral estimation due to Lang and McClellan, which were adapted by Steinhardt, Goodrich and Roberts for minimum-norm spectral estimation. Cole`s extension of their work provides a representation for minimum-norm estimates of a class of generalized transformsmore » in terms of general correlation data (not just DFT`s of autocorrelation lags, as in spectral estimation). One virtue of this great generality is that it includes the inverse DWT. 20 refs.« less

Total decay and transition rates from LQCD

NASA Astrophysics Data System (ADS)

Hansen, Maxwell T.; Meyer, Harvey B.; Robaina, Daniel

2018-03-01

We present a new technique for extracting total transition rates into final states with any number of hadrons from lattice QCD. The method involves constructing a finite-volume Euclidean four-point function whose corresponding infinite-volume spectral function gives access to the decay and transition rates into all allowed final states. The inverse problem of calculating the spectral function is solved via the Backus-Gilbert method, which automatically includes a smoothing procedure. This smoothing is in fact required so that an infinite-volume limit of the spectral function exists. Using a numerical toy example we find that reasonable precision can be achieved with realistic lattice data. In addition, we discuss possible extensions of our approach and, as an example application, prospects for applying the formalism to study the onset of deep-inelastic scattering. More details are given in the published version of this work, Ref. [1].

A catalog of M-type star candidates in the LAMOST data release 1

NASA Astrophysics Data System (ADS)

Zhong, Jing; Lépine, Sébastien; Li, Jing; Chen, Li; Hou, Jinliang

2016-08-01

In this work, we present a set of M-type star candidates selected from the LAMOST DR1. A discrimination method with the spectral index diagram is used to separate M giants and M dwarfs. Then, we have successfully assembled a set of M giants templates from M0 to M6, using the spectra identified from the LAMOST spectral database. After combining the M dwarf templates in Zhong et al. (2015a) and the new created M giant templates, we use the M-type spectral library to perform the template-fit method to classify and identify M-type stars in the LAMOST DR1. A catalog of M-type star candidates including 8639 M giants and 101690 M dwarfs/subdwarfs is provided. As an additional results, we also present other fundamental parameters like proper motion, photometry, radial velocity and spectroscopic distance.

Some spectral approximation of one-dimensional fourth-order problems

NASA Technical Reports Server (NTRS)

Bernardi, Christine; Maday, Yvon

1989-01-01

Some spectral type collocation method well suited for the approximation of fourth-order systems are proposed. The model problem is the biharmonic equation, in one and two dimensions when the boundary conditions are periodic in one direction. It is proved that the standard Gauss-Lobatto nodes are not the best choice for the collocation points. Then, a new set of nodes related to some generalized Gauss type quadrature formulas is proposed. Also provided is a complete analysis of these formulas including some new issues about the asymptotic behavior of the weights and we apply these results to the analysis of the collocation method.

Terahertz spectral unmixing based method for identifying gastric cancer

NASA Astrophysics Data System (ADS)

Cao, Yuqi; Huang, Pingjie; Li, Xian; Ge, Weiting; Hou, Dibo; Zhang, Guangxin

2018-02-01

At present, many researchers are exploring biological tissue inspection using terahertz time-domain spectroscopy (THz-TDS) techniques. In this study, based on a modified hard modeling factor analysis method, terahertz spectral unmixing was applied to investigate the relationships between the absorption spectra in THz-TDS and certain biomarkers of gastric cancer in order to systematically identify gastric cancer. A probability distribution and box plot were used to extract the distinctive peaks that indicate carcinogenesis, and the corresponding weight distributions were used to discriminate the tissue types. The results of this work indicate that terahertz techniques have the potential to detect different levels of cancer, including benign tumors and polyps.

Using Finite Element and Eigenmode Expansion Methods to Investigate the Periodic and Spectral Characteristic of Superstructure Fiber Bragg Gratings

PubMed Central

He, Yue-Jing; Hung, Wei-Chih; Lai, Zhe-Ping

2016-01-01

In this study, a numerical simulation method was employed to investigate and analyze superstructure fiber Bragg gratings (SFBGs) with five duty cycles (50%, 33.33%, 14.28%, 12.5%, and 10%). This study focuses on demonstrating the relevance between design period and spectral characteristics of SFBGs (in the form of graphics) for SFBGs of all duty cycles. Compared with complicated and hard-to-learn conventional coupled-mode theory, the result of the present study may assist beginner and expert designers in understanding the basic application aspects, optical characteristics, and design techniques of SFBGs, thereby indirectly lowering the physical concepts and mathematical skills required for entering the design field. To effectively improve the accuracy of overall computational performance and numerical calculations and to shorten the gap between simulation results and actual production, this study integrated a perfectly matched layer (PML), perfectly reflecting boundary (PRB), object meshing method (OMM), and boundary meshing method (BMM) into the finite element method (FEM) and eigenmode expansion method (EEM). The integrated method enables designers to easily and flexibly design optical fiber communication systems that conform to the specific spectral characteristic by using the simulation data in this paper, which includes bandwidth, number of channels, and band gap size. PMID:26861322

Plasma emission spectroscopy method of tumor therapy

DOEpatents

Fleming, Kevin J.

1997-01-01

Disclosed are a method and apparatus for performing photon diagnostics using a portable and durable apparatus which incorporates the use of a remote sensing probe in fiberoptic communication with an interferometer or spectrometer. Also disclosed are applications for the apparatus including optically measuring high velocities and analyzing plasma/emission spectral characteristics.

Method and device for predicting wavelength dependent radiation influences in thermal systems

DOEpatents

Kee, Robert J.; Ting, Aili

1996-01-01

A method and apparatus for predicting the spectral (wavelength-dependent) radiation transport in thermal systems including interaction by the radiation with partially transmitting medium. The predicted model of the thermal system is used to design and control the thermal system. The predictions are well suited to be implemented in design and control of rapid thermal processing (RTP) reactors. The method involves generating a spectral thermal radiation transport model of an RTP reactor. The method also involves specifying a desired wafer time dependent temperature profile. The method further involves calculating an inverse of the generated model using the desired wafer time dependent temperature to determine heating element parameters required to produce the desired profile. The method also involves controlling the heating elements of the RTP reactor in accordance with the heating element parameters to heat the wafer in accordance with the desired profile.

[A new non-contact method based on relative spectral intensity for determining junction temperature of LED].

PubMed

Qiu, Xi-Zhen; Zhang, Fang-Hui

2013-01-01

The high-power white LED was prepared based on the high thermal conductivity aluminum, blue chips and YAG phosphor. By studying the spectral of different junction temperature, we found that the radiation spectrum of white LED has a minimum at 485 nm. The radiation intensity at this wavelength and the junction temperature show a good linear relationship. The LED junction temperature was measured based on the formula of relative spectral intensity and junction temperature. The result measured by radiation intensity method was compared with the forward voltage method and spectral method. The experiment results reveal that the junction temperature measured by this method was no more than 2 degrees C compared with the forward voltage method. It maintains the accuracy of the forward voltage method and overcomes the small spectral shift of spectral method, which brings the shortcoming on the results. It also had the advantages of practical, efficient and intuitive, noncontact measurement, and non-destruction to the lamp structure.

A High-Order Finite Spectral Volume Method for Conservation Laws on Unstructured Grids

NASA Technical Reports Server (NTRS)

Wang, Z. J.; Liu, Yen; Kwak, Dochan (Technical Monitor)

2001-01-01

A time accurate, high-order, conservative, yet efficient method named Finite Spectral Volume (FSV) is developed for conservation laws on unstructured grids. The concept of a 'spectral volume' is introduced to achieve high-order accuracy in an efficient manner similar to spectral element and multi-domain spectral methods. In addition, each spectral volume is further sub-divided into control volumes (CVs), and cell-averaged data from these control volumes is used to reconstruct a high-order approximation in the spectral volume. Riemann solvers are used to compute the fluxes at spectral volume boundaries. Then cell-averaged state variables in the control volumes are updated independently. Furthermore, TVD (Total Variation Diminishing) and TVB (Total Variation Bounded) limiters are introduced in the FSV method to remove/reduce spurious oscillations near discontinuities. A very desirable feature of the FSV method is that the reconstruction is carried out only once, and analytically, and is the same for all cells of the same type, and that the reconstruction stencil is always non-singular, in contrast to the memory and CPU-intensive reconstruction in a high-order finite volume (FV) method. Discussions are made concerning why the FSV method is significantly more efficient than high-order finite volume and the Discontinuous Galerkin (DG) methods. Fundamental properties of the FSV method are studied and high-order accuracy is demonstrated for several model problems with and without discontinuities.

Nanophotonic Image Sensors

PubMed Central

Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R. S.

2016-01-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial‐based THz image sensors, filter‐free nanowire image sensors and nanostructured‐based multispectral image sensors. This novel combination of cutting edge photonics research and well‐developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. PMID:27239941

Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

NASA Astrophysics Data System (ADS)

Garbanzo-Salas, Marcial; Hocking, Wayne. K.

2015-09-01

In recent years, adaptive (data dependent) methods have been introduced into many areas where Fourier spectral analysis has traditionally been used. Although the data-dependent methods are often advanced as being superior to Fourier methods, they do require some finesse in choosing the order of the relevant filters. In performing comparisons, we have found some concerns about the mappings, particularly when related to cases involving many spectral lines or even continuous spectral signals. Using numerical simulations, several comparisons between Fourier transform procedures and minimum variance method (MVM) have been performed. For multiple frequency signals, the MVM resolves most of the frequency content only for filters that have more degrees of freedom than the number of distinct spectral lines in the signal. In the case of Gaussian spectral approximation, MVM will always underestimate the width, and can misappropriate the location of spectral line in some circumstances. Large filters can be used to improve results with multiple frequency signals, but are computationally inefficient. Significant biases can occur when using MVM to study spectral information or echo power from the atmosphere. Artifacts and artificial narrowing of turbulent layers is one such impact.

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

PubMed

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2011-04-01

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

Spectral methods on arbitrary grids

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Gottlieb, David

1995-01-01

Stable and spectrally accurate numerical methods are constructed on arbitrary grids for partial differential equations. These new methods are equivalent to conventional spectral methods but do not rely on specific grid distributions. Specifically, we show how to implement Legendre Galerkin, Legendre collocation, and Laguerre Galerkin methodology on arbitrary grids.

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.

Spectral density method to Anderson-Holstein model

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

Chebrolu, Narasimha Raju, E-mail: narasimharaju.phy@gmail.com; Chatterjee, Ashok

Two-parameter spectral density function of a magnetic impurity electron in a non-magnetic metal is calculated within the framework of the Anderson-Holstein model using the spectral density approximation method. The effect of electron-phonon interaction on the spectral function is investigated.

Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Chehata, N.; Briottet, X.; Paparoditis, N.

2016-06-01

In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000-2400 nm) to material classification was also shown.

Spectral line polarimetry with a channeled polarimeter.

PubMed

van Harten, Gerard; Snik, Frans; Rietjens, Jeroen H H; Martijn Smit, J; Keller, Christoph U

2014-07-01

Channeled spectropolarimetry or spectral polarization modulation is an accurate technique for measuring the continuum polarization in one shot with no moving parts. We show how a dual-beam implementation also enables spectral line polarimetry at the intrinsic resolution, as in a classic beam-splitting polarimeter. Recording redundant polarization information in the two spectrally modulated beams of a polarizing beam-splitter even provides the possibility to perform a postfacto differential transmission correction that improves the accuracy of the spectral line polarimetry. We perform an error analysis to compare the accuracy of spectral line polarimetry to continuum polarimetry, degraded by a residual dark signal and differential transmission, as well as to quantify the impact of the transmission correction. We demonstrate the new techniques with a blue sky polarization measurement around the oxygen A absorption band using the groundSPEX instrument, yielding a polarization in the deepest part of the band of 0.160±0.010, significantly different from the polarization in the continuum of 0.2284±0.0004. The presented methods are applicable to any dual-beam channeled polarimeter, including implementations for snapshot imaging polarimetry.

Multispectral analysis tools can increase utility of RGB color images in histology

NASA Astrophysics Data System (ADS)

Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

2018-04-01

Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

Spectral fluorescent properties of tissues in vivo with excitation in the red wavelength range

NASA Astrophysics Data System (ADS)

Stratonnikov, Alexander A.; Loschenov, Victor B.; Klimov, D. V.; Edinac, N. E.; Wolnukhin, V. A.; Strashkevich, I. A.

1997-12-01

The spectral fluorescence analysis is a promising method for differential tissue diagnostic. Usually the UV and visible light is used for fluorescence excitation with emission registration in the visible wavelength range. The light penetration length in this wavelength range is very small allowing one to analyze only the surface region of the tissue. Here we present the tissue fluorescent spectra in vivo excited in the red wavelength region. As excitation light source we used compact He-Ne laser (632.8 nm) and observed the fluorescence in 650 - 800 nm spectral range. The various tissues including normal skin, psoriasis, tumors, necrosis as well as photosensitized tissues have been measured.

Fiberoptic probe and system for spectral measurements

DOEpatents

Dai, S.; Young, J.P.

1998-10-13

A fused fiberoptic probe, a system, method and embodiments thereof for conducting spectral measurements are disclosed. The fused fiberoptic probe comprises a probe tip having a specific geometrical configuration, an exciting optical fiber and at least one collection optical fiber fused within a housing, preferably silica. The specific geometrical configurations in which the probe tip can be shaped include a slanted probe tip with an angle greater than 0{degree}, an inverted cone-shaped probe tip, and a lens head. 12 figs.

Optoelectronic semiconductor device and method of fabrication

DOEpatents

Cui, Yi; Zhu, Jia; Hsu, Ching-Mei; Fan, Shanhui; Yu, Zongfu

2014-11-25

An optoelectronic device comprising an optically active layer that includes a plurality of domes is presented. The plurality of domes is arrayed in two dimensions having a periodicity in each dimension that is less than or comparable with the shortest wavelength in a spectral range of interest. By virtue of the plurality of domes, the optoelectronic device achieves high performance. A solar cell having high energy-conversion efficiency, improved absorption over the spectral range of interest, and an improved acceptance angle is presented as an exemplary device.

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy.

PubMed

Zelyak, O; Fallone, B G; St-Aubin, J

2017-12-14

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation.

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy

NASA Astrophysics Data System (ADS)

Zelyak, O.; Fallone, B. G.; St-Aubin, J.

2018-01-01

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation.

Corrigendum to "Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy".

PubMed

Zelyak, Oleksandr; Fallone, B Gino; St-Aubin, Joel

2018-03-12

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation. © 2018 Institute of Physics and Engineering in Medicine.

APPLIED REMOTE SENSING

EPA Science Inventory

Remote Sensing is a scientific discipline of non-contact monitoring. It includes a range of technologies that span from aerial photography to advanced spectral imaging and analytical methods. This Session is designed to demonstrate contemporary practical applications of remote se...

Physics Notes.

ERIC Educational Resources Information Center

School Science Review, 1982

1982-01-01

Outlines methodology, demonstrations, and materials including: an inexpensive wave machine; speed of sound in carbon dioxide; diffraction grating method for measuring spectral line wavelength; linear electronic thermometer; analogy for bromine diffusion; direct reading refractice index meter; inexpensive integrated circuit spectrophotometer; and…

A new approach for the calculation of response spectral density of a linear stationary random multidegree of freedom system

NASA Astrophysics Data System (ADS)

Sharan, A. M.; Sankar, S.; Sankar, T. S.

1982-08-01

A new approach for the calculation of response spectral density for a linear stationary random multidegree of freedom system is presented. The method is based on modifying the stochastic dynamic equations of the system by using a set of auxiliary variables. The response spectral density matrix obtained by using this new approach contains the spectral densities and the cross-spectral densities of the system generalized displacements and velocities. The new method requires significantly less computation time as compared to the conventional method for calculating response spectral densities. Two numerical examples are presented to compare quantitatively the computation time.

Comparison Study of Regularizations in Spectral Computed Tomography Reconstruction

NASA Astrophysics Data System (ADS)

Salehjahromi, Morteza; Zhang, Yanbo; Yu, Hengyong

2018-12-01

The energy-resolving photon-counting detectors in spectral computed tomography (CT) can acquire projections of an object in different energy channels. In other words, they are able to reliably distinguish the received photon energies. These detectors lead to the emerging spectral CT, which is also called multi-energy CT, energy-selective CT, color CT, etc. Spectral CT can provide additional information in comparison with the conventional CT in which energy integrating detectors are used to acquire polychromatic projections of an object being investigated. The measurements obtained by X-ray CT detectors are noisy in reality, especially in spectral CT where the photon number is low in each energy channel. Therefore, some regularization should be applied to obtain a better image quality for this ill-posed problem in spectral CT image reconstruction. Quadratic-based regularizations are not often satisfactory as they blur the edges in the reconstructed images. As a result, different edge-preserving regularization methods have been adopted for reconstructing high quality images in the last decade. In this work, we numerically evaluate the performance of different regularizers in spectral CT, including total variation, non-local means and anisotropic diffusion. The goal is to provide some practical guidance to accurately reconstruct the attenuation distribution in each energy channel of the spectral CT data.

Newly Diagnosed Breast Cancer: Comparison of Contrast-enhanced Spectral Mammography and Breast MR Imaging in the Evaluation of Extent of Disease.

PubMed

Lee-Felker, Stephanie A; Tekchandani, Leena; Thomas, Mariam; Gupta, Esha; Andrews-Tang, Denise; Roth, Antoinette; Sayre, James; Rahbar, Guita

2017-11-01

Purpose To compare the diagnostic performances of contrast material-enhanced spectral mammography and breast magnetic resonance (MR) imaging in the detection of index and secondary cancers in women with newly diagnosed breast cancer by using histologic or imaging follow-up as the standard of reference. Materials and Methods This institutional review board-approved, HIPAA-compliant, retrospective study included 52 women who underwent breast MR imaging and contrast-enhanced spectral mammography for newly diagnosed unilateral breast cancer between March 2014 and October 2015. Of those 52 patients, 46 were referred for contrast-enhanced spectral mammography and targeted ultrasonography because they had additional suspicious lesions at MR imaging. In six of the 52 patients, breast cancer had been diagnosed at an outside institution. These patients were referred for contrast-enhanced spectral mammography and targeted US as part of diagnostic imaging. Images from contrast-enhanced spectral mammography were analyzed by two fellowship-trained breast imagers with 2.5 years of experience with contrast-enhanced spectral mammography. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated for both imaging modalities and compared by using the Bennett statistic. Results Fifty-two women with 120 breast lesions were included for analysis (mean age, 50 years; range, 29-73 years). Contrast-enhanced spectral mammography had similar sensitivity to MR imaging (94% [66 of 70 lesions] vs 99% [69 of 70 lesions]), a significantly higher PPV than MR imaging (93% [66 of 71 lesions] vs 60% [69 of 115 lesions]), and fewer false-positive findings than MR imaging (five vs 45) (P < .001 for all results). In addition, contrast-enhanced spectral mammography depicted 11 of the 11 secondary cancers (100%) and MR imaging depicted 10 (91%). Conclusion Contrast-enhanced spectral mammography is potentially as sensitive as MR imaging in the evaluation of extent of disease in newly diagnosed breast cancer, with a higher PPV. © RSNA, 2017.

An adaptive band selection method for dimension reduction of hyper-spectral remote sensing image

NASA Astrophysics Data System (ADS)

Yu, Zhijie; Yu, Hui; Wang, Chen-sheng

2014-11-01

Hyper-spectral remote sensing data can be acquired by imaging the same area with multiple wavelengths, and it normally consists of hundreds of band-images. Hyper-spectral images can not only provide spatial information but also high resolution spectral information, and it has been widely used in environment monitoring, mineral investigation and military reconnaissance. However, because of the corresponding large data volume, it is very difficult to transmit and store Hyper-spectral images. Hyper-spectral image dimensional reduction technique is desired to resolve this problem. Because of the High relation and high redundancy of the hyper-spectral bands, it is very feasible that applying the dimensional reduction method to compress the data volume. This paper proposed a novel band selection-based dimension reduction method which can adaptively select the bands which contain more information and details. The proposed method is based on the principal component analysis (PCA), and then computes the index corresponding to every band. The indexes obtained are then ranked in order of magnitude from large to small. Based on the threshold, system can adaptively and reasonably select the bands. The proposed method can overcome the shortcomings induced by transform-based dimension reduction method and prevent the original spectral information from being lost. The performance of the proposed method has been validated by implementing several experiments. The experimental results show that the proposed algorithm can reduce the dimensions of hyper-spectral image with little information loss by adaptively selecting the band images.

Two-Flux and Green's Function Method for Transient Radiative Transfer in a Semi-Transparent Layer

NASA Technical Reports Server (NTRS)

Siegel, Robert

1995-01-01

A method using a Green's function is developed for computing transient temperatures in a semitransparent layer by using the two-flux method coupled with the transient energy equation. Each boundary of the layer is exposed to a hot or cold radiative environment, and is heated or cooled by convection. The layer refractive index is larger than one, and the effect of internal reflections is included with the boundaries assumed diffuse. The analysis accounts for internal emission, absorption, heat conduction, and isotropic scattering. Spectrally dependent radiative properties are included, and transient results are given to illustrate two-band spectral behavior with optically thin and thick bands. Transient results using the present Green's function method are verified for a gray layer by comparison with a finite difference solution of the exact radiative transfer equations; excellent agreement is obtained. The present method requires only moderate computing times and incorporates isotropic scattering without additional complexity. Typical temperature distributions are given to illustrate application of the method by examining the effect of strong radiative heating on one side of a layer with convective cooling on the other side, and the interaction of strong convective heating with radiative cooling from the layer interior.

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.

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?

Spectral theory of extreme statistics in birth-death systems

NASA Astrophysics Data System (ADS)

Meerson, Baruch

2008-03-01

Statistics of rare events, or large deviations, in chemical reactions and systems of birth-death type have attracted a great deal of interest in many areas of science including cell biochemistry, astrochemistry, epidemiology, population biology, etc. Large deviations become of vital importance when discrete (non-continuum) nature of a population of ``particles'' (molecules, bacteria, cells, animals or even humans) and stochastic character of interactions can drive the population to extinction. I will briefly review the novel spectral method [1-3] for calculating the extreme statistics of a broad class of birth-death processes and reactions involving a single species. The spectral method combines the probability generating function formalism with the Sturm-Liouville theory of linear differential operators. It involves a controlled perturbative treatment based on a natural large parameter of the problem: the average number of particles/individuals in a stationary or metastable state. For extinction (the first passage) problems the method yields accurate results for the extinction statistics and for the quasi-stationary probability distribution, including the tails, of metastable states. I will demonstrate the power of the method on the example of a branching and annihilation reaction, A ->-2.8mm2mm2A,,A ->-2.8mm2mm , representative of a rather general class of processes. *M. Assaf and B. Meerson, Phys. Rev. Lett. 97, 200602 (2006). *M. Assaf and B. Meerson, Phys. Rev. E 74, 041115 (2006). *M. Assaf and B. Meerson, Phys. Rev. E 75, 031122 (2007).

Plasma emission spectroscopy method of tumor therapy

DOEpatents

Fleming, K.J.

1997-03-11

Disclosed are a method and apparatus for performing photon diagnostics using a portable and durable apparatus which incorporates the use of a remote sensing probe in fiberoptic communication with an interferometer or spectrometer. Also disclosed are applications for the apparatus including optically measuring high velocities and analyzing plasma/emission spectral characteristics. 6 figs.

Sharpening advanced land imager multispectral data using a sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2005-01-01

The Advanced Land Imager (ALI) instrument on NASA's Earth Observing One (EO-1) satellite provides for nine spectral bands at 30m ground sample distance (GSD) and a 10m GSD panchromatic band. This report describes an image sharpening technique where the higher spatial resolution information of the panchromatic band is used to increase the spatial resolution of ALI multispectral (MS) data. To preserve the spectral characteristics, this technique combines reported deconvolution deblurring methods for the MS data with highpass filter-based fusion methods for the Pan data. The deblurring process uses the point spread function (PSF) model of the ALI sensor. Information includes calculation of the PSF from pre-launch calibration data. Performance was evaluated using simulated ALI MS data generated by degrading the spatial resolution of high resolution IKONOS satellite MS data. A quantitative measure of performance was the error between sharpened MS data and high resolution reference. This report also compares performance with that of a reported method that includes PSF information. Preliminary results indicate improved sharpening with the method reported here.

[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.

Spectral Target Detection using Schroedinger Eigenmaps

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.

Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and those similar pixels are clustered in a predictable region of the low-dimensional representation is used to define a decision rule that allows one to identify target pixels over the rest of pixels in a given image. In addition, a knowledge propagation scheme is used to combine spectral and spatial information as a means to propagate the "potential constraints" to nearby points. The propagation scheme is introduced to reinforce weak connections and improve the separability between most of the target pixels and the background. Experiments using different HSI data sets are carried out in order to test the proposed methodology. The assessment is performed from a quantitative and qualitative point of view, and by comparing the SE-based methodology against two other detection methodologies that use linear/non-linear algorithms as transformations and the well-known Adaptive Coherence/Cosine Estimator (ACE) detector. Overall results show that the SE-based detector outperforms the other two detection methodologies, which indicates the usefulness of the SE transformation in spectral target detection problems.

Spectral Tuning of Killer Whale (Orcinus orca) Rhodopsin: Evidence for Positive Selection and Functional Adaptation in a Cetacean Visual Pigment.

PubMed

Dungan, Sarah Z; Kosyakov, Alexander; Chang, Belinda S W

2016-02-01

Cetaceans have undergone a remarkable evolutionary transition that was accompanied by many sensory adaptations, including modification of the visual system for underwater environments. Recent sequencing of cetacean genomes has made it possible to begin exploring the molecular basis of these adaptations. In this study we use in vitro expression methods to experimentally characterize the first step of the visual transduction cascade, the light activation of rhodopsin, for the killer whale. To investigate the spectral effects of amino acid substitutions thought to correspond with absorbance shifts relative to terrestrial mammals, we used the orca gene as a background for the first site-directed mutagenesis experiments in a cetacean rhodopsin. The S292A mutation had the largest effect, and was responsible for the majority of the spectral difference between killer whale and bovine (terrestrial) rhodopsin. Using codon-based likelihood models, we also found significant evidence for positive selection in cetacean rhodopsin sequences, including on spectral tuning sites we experimentally mutated. We then investigated patterns of ecological divergence that may be correlated with rhodopsin functional variation by using a series of clade models that partitioned the data set according to phylogeny, habitat, and foraging depth zone. Only the model partitioning according to depth was significant. This suggests that foraging dives might be a selective regime influencing cetacean rhodopsin divergence, and our experimental results indicate that spectral tuning may be playing an adaptive role in this process. Our study demonstrates that combining computational and experimental methods is crucial for gaining insight into the selection pressures underlying molecular evolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Chandra Source Catalog 2.0: Spectral Properties

NASA Astrophysics Data System (ADS)

McCollough, Michael L.; Siemiginowska, Aneta; Burke, Douglas; Nowak, Michael A.; Primini, Francis Anthony; Laurino, Omar; Nguyen, Dan T.; Allen, Christopher E.; Anderson, Craig S.; Budynkiewicz, Jamie A.; Chen, Judy C.; Civano, Francesca Maria; D'Abrusco, Raffaele; Doe, Stephen M.; Evans, Ian N.; Evans, Janet D.; Fabbiano, Giuseppina; Gibbs, Danny G., II; Glotfelty, Kenny J.; Graessle, Dale E.; Grier, John D.; Hain, Roger; Hall, Diane M.; Harbo, Peter N.; Houck, John C.; Lauer, Jennifer L.; Lee, Nicholas P.; Martínez-Galarza, Juan Rafael; McDowell, Jonathan C.; Miller, Joseph; McLaughlin, Warren; Morgan, Douglas L.; Mossman, Amy E.; Nichols, Joy S.; Paxson, Charles; Plummer, David A.; Rots, Arnold H.; Sundheim, Beth A.; Tibbetts, Michael; Van Stone, David W.; Zografou, Panagoula; Chandra Source Catalog Team

2018-01-01

The second release of the Chandra Source Catalog (CSC) contains all sources identified from sixteen years' worth of publicly accessible observations. The vast majority of these sources have been observed with the ACIS detector and have spectral information in 0.5-7 keV energy range. Here we describe the methods used to automatically derive spectral properties for each source detected by the standard processing pipeline and included in the final CSC. The sources with high signal to noise ratio (exceeding 150 net counts) were fit in Sherpa (the modeling and fitting application from the Chandra Interactive Analysis of Observations package) using wstat as a fit statistic and Bayesian draws method to determine errors. Three models were fit to each source: an absorbed power-law, blackbody, and Bremsstrahlung emission. The fitted parameter values for the power-law, blackbody, and Bremsstrahlung models were included in the catalog with the calculated flux for each model. The CSC also provides the source energy fluxes computed from the normalizations of predefined absorbed power-law, black-body, Bremsstrahlung, and APEC models needed to match the observed net X-ray counts. For sources that have been observed multiple times we performed a Bayesian Blocks analysis will have been performed (see the Primini et al. poster) and the most significant block will have a joint fit performed for the mentioned spectral models. In addition, we provide access to data products for each source: a file with source spectrum, the background spectrum, and the spectral response of the detector. Hardness ratios were calculated for each source between pairs of energy bands (soft, medium and hard). This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

On the electromagnetic scattering from infinite rectangular conducting grids

NASA Technical Reports Server (NTRS)

Christodoulou, C.

1985-01-01

The study and development of two numerical techniques for the analysis of electromagnetic scattering from a rectangular wire mesh are described. Both techniques follow from one basic formulation and they are both solved in the spectral domain. These techniques were developed as a result of an investigation towards more efficient numerical computation for mesh scattering. These techniques are efficient for the following reasons: (a1) make use of the Fast Fourier Transform; (b2) they avoid any convolution problems by converting integrodifferential equations into algebraic equations; and (c3) they do not require inversions of any matrices. The first method, the SIT or Spectral Iteration Technique, is applied for regions where the spacing between wires is not less than two wavelengths. The second method, the SDCG or Spectral Domain Conjugate Gradient approach, can be used for any spacing between adjacent wires. A study of electromagnetic wave properties, such as reflection coefficient, induced currents and aperture fields, as functions of frequency, angle of incidence, polarization and thickness of wires is presented. Examples and comparisons or results with other methods are also included to support the validity of the new algorithms.

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.

Une nouvelle méthode de cartographie de la région d'Oran (Algérie) à l'aide de la télédétection multispectrale

NASA Astrophysics Data System (ADS)

Laoufi, Fatiha; Belbachir, Ahmed-Hafid; Benabadji, Noureddine; Zanoun, Abdelouahab

2011-10-01

We have mapped the region of Oran, Algeria, using multispectral remote sensing with different resolutions. For the identification of objects on the ground using their spectral signatures, two methods were applied to images from SPOT, LANDSAT, IRS-1 C and ASTER. The first one is called Base Rule method (BR method) and is based on a set of rules that must be met at each pixel in the different bands reflectance calibrated and henceforth it is assigned to a given class. The construction of these rules is based on the spectral profiles of popular classes in the scene studied. The second one is called Spectral Angle Mapper method (SAM method) and is based on the direct calculation of the spectral angle between the target vector representing the spectral profile of the desired class and the pixel vector whose components are numbered accounts in the different bands of the calibrated image reflectance. This new method was performed using PCSATWIN software developed by our own laboratory LAAR. After collecting a library of spectral signatures with multiple libraries, a detailed study of the principles and physical processes that can influence the spectral signature has been conducted. The final goal is to establish the range of variation of a spectral profile of a well-defined class and therefore to get precise bases for spectral rules. From the results we have obtained, we find that the supervised classification of these pixels by BR method derived from spectral signatures reduces the uncertainty associated with identifying objects by enhancing significantly the percentage of correct classification with very distinct classes.

Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic

USGS Publications Warehouse

Chavez, P.S.; Sides, S.C.; Anderson, J.A.

1991-01-01

The merging of multisensor image data is becoming a widely used procedure because of the complementary nature of various data sets. Ideally, the method used to merge data sets with high-spatial and high-spectral resolution should not distort the spectral characteristics of the high-spectral resolution data. This paper compares the results of three different methods used to merge the information contents of the Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) panchromatic data. The comparison is based on spectral characteristics and is made using statistical, visual, and graphical analyses of the results. The three methods used to merge the information contents of the Landsat TM and SPOT panchromatic data were the Hue-Intensity-Saturation (HIS), Principal Component Analysis (PCA), and High-Pass Filter (HPF) procedures. The HIS method distorted the spectral characteristics of the data the most. The HPF method distorted the spectral characteristics the least; the distortions were minimal and difficult to detect. -Authors

A Single Chiroptical Spectroscopic Method May Not Be Able To Establish the Absolute Configurations of Diastereomers: Dimethylesters of Hibiscus and Garcinia Acids

PubMed Central

Polavarapu, Prasad L.; Donahue, Emily A.; Shanmugam, Ganesh; Scalmani, Giovanni; Hawkins, Edward K.; Rizzo, Carmelo; Ibnusaud, Ibrahim; Thomas, Grace; Habel, Deenamma; Sebastian, Dellamol

2013-01-01

Electronic circular dichroism (ECD), optical rotatory dispersion (ORD), and vibrational circular dichroism (VCD) spectra of hibiscus acid dimethyl ester have been measured and analyzed in combination with quantum chemical calculations of corresponding spectra. These results, along with those reported previously for garcinia acid dimethyl ester, reveal that none of these three (ECD, ORD, or VCD) spectroscopic methods, in isolation, can unequivocally establish the absolute configurations of diastereomers. This deficiency is eliminated when a combined spectral analysis of either ECD and VCD or ORD and VCD methods is used. It is also found that the ambiguities in the assignment of absolute configurations of diastereomers may also be overcome when unpolarized vibrational absorption is included in the spectral analysis. PMID:21568330

Methods and systems for remote detection of gases

DOEpatents

Johnson, Timothy J.

2007-11-27

Novel systems and methods for remotely detecting at least one constituent of a gas via infrared detection are provided. A system includes at least one extended source of broadband infrared radiation and a spectrally sensitive receiver positioned remotely from the source. The source and the receiver are oriented such that a surface of the source is in the field of view of the receiver. The source includes a heating component thermally coupled to the surface, and the heating component is configured to heat the surface to a temperature above ambient temperature. The receiver is operable to collect spectral infrared absorption data representative of a gas present between the source and the receiver. The invention advantageously overcomes significant difficulties associated with active infrared detection techniques known in the art, and provides an infrared detection technique with a much greater sensitivity than passive infrared detection techniques known in the art.

Methods and systems for remote detection of gases

DOEpatents

Johnson, Timothy J

2012-09-18

Novel systems and methods for remotely detecting at least one constituent of a gas via infrared detection are provided. A system includes at least one extended source of broadband infrared radiation and a spectrally sensitive receiver positioned remotely from the source. The source and the receiver are oriented such that a surface of the source is in the field of view of the receiver. The source includes a heating component thermally coupled to the surface, and the heating component is configured to heat the surface to a temperature above ambient temperature. The receiver is operable to collect spectral infrared absorption data representative of a gas present between the source and the receiver. The invention advantageously overcomes significant difficulties associated with active infrared detection techniques known in the art, and provides an infrared detection technique with a much greater sensitivity than passive infrared detection techniques known in the art.

Group refractive index reconstruction with broadband interferometric confocal microscopy

PubMed Central

Marks, Daniel L.; Schlachter, Simon C.; Zysk, Adam M.; Boppart, Stephen A.

2010-01-01

We propose a novel method of measuring the group refractive index of biological tissues at the micrometer scale. The technique utilizes a broadband confocal microscope embedded into a Mach–Zehnder interferometer, with which spectral interferograms are measured as the sample is translated through the focus of the beam. The method does not require phase unwrapping and is insensitive to vibrations in the sample and reference arms. High measurement stability is achieved because a single spectral interferogram contains all the information necessary to compute the optical path delay of the beam transmitted through the sample. Included are a physical framework defining the forward problem, linear solutions to the inverse problem, and simulated images of biologically relevant phantoms. PMID:18451922

Implementation and Testing of Turbulence Models for the F18-HARV Simulation

NASA Technical Reports Server (NTRS)

Yeager, Jessie C.

1998-01-01

This report presents three methods of implementing the Dryden power spectral density model for atmospheric turbulence. Included are the equations which define the three methods and computer source code written in Advanced Continuous Simulation Language to implement the equations. Time-history plots and sample statistics of simulated turbulence results from executing the code in a test program are also presented. Power spectral densities were computed for sample sequences of turbulence and are plotted for comparison with the Dryden spectra. The three model implementations were installed in a nonlinear six-degree-of-freedom simulation of the High Alpha Research Vehicle airplane. Aircraft simulation responses to turbulence generated with the three implementations are presented as plots.

FSD: Frequency Space Differential measurement of CMB spectral distortions

NASA Astrophysics Data System (ADS)

Mukherjee, Suvodip; Silk, Joseph; Wandelt, Benjamin D.

2018-07-01

Although the cosmic microwave background (CMB) agrees with a perfect blackbody spectrum within the current experimental limits, it is expected to exhibit certain spectral distortions with known spectral properties. We propose a new method Frequency Space Differential (FSD) to measure the spectral distortions in the CMB spectrum by using the inter-frequency differences of the brightness temperature. The difference between the observed CMB temperature at different frequencies must agree with the frequency derivative of the blackbody spectrum in the absence of any distortion. However, in the presence of spectral distortions, the measured inter-frequency differences would also exhibit deviations from blackbody that can be modelled for known sources of spectral distortions like y and μ. Our technique uses FSD information for the CMB blackbody, y, μ, or any other sources of spectral distortions to model the observed signal. Successful application of this method in future CMB missions can provide an alternative method to extract spectral distortion signals and can potentially make it feasible to measure spectral distortions without an internal blackbody calibrator.

Dimension Reduction of Hyperspectral Data on Beowulf Clusters

NASA Technical Reports Server (NTRS)

El-Ghazawi, Tarek

2000-01-01

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operation. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold a great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, which is used widely in remote sensing, is the Principal Components Analysis (PCA). In light of the growing number of spectral channels of modern instruments, the paper reports on the development of a parallel PCA and its implementation on two Beowulf cluster configurations, on with fast Ethernet switch and the other is with a Myrinet interconnection.

Spectral collocation methods

NASA Technical Reports Server (NTRS)

Hussaini, M. Y.; Kopriva, D. A.; Patera, A. T.

1987-01-01

This review covers the theory and application of spectral collocation methods. Section 1 describes the fundamentals, and summarizes results pertaining to spectral approximations of functions. Some stability and convergence results are presented for simple elliptic, parabolic, and hyperbolic equations. Applications of these methods to fluid dynamics problems are discussed in Section 2.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Evaluation of AMOEBA: a spectral-spatial classification method

USGS Publications Warehouse

Jenson, Susan K.; Loveland, Thomas R.; Bryant, J.

1982-01-01

Muitispectral remotely sensed images have been treated as arbitrary multivariate spectral data for purposes of clustering and classifying. However, the spatial properties of image data can also be exploited. AMOEBA is a clustering and classification method that is based on a spatially derived model for image data. In an evaluation test, Landsat data were classified with both AMOEBA and a widely used spectral classifier. The test showed that irrigated crop types can be classified as accurately with the AMOEBA method as with the generally used spectral method ISOCLS; the AMOEBA method, however, requires less computer time.

Advances and future directions of research on spectral methods

NASA Technical Reports Server (NTRS)

Patera, A. T.

1986-01-01

Recent advances in spectral methods are briefly reviewed and characterized with respect to their convergence and computational complexity. Classical finite element and spectral approaches are then compared, and spectral element (or p-type finite element) approximations are introduced. The method is applied to the full Navier-Stokes equations, and examples are given of the application of the technique to several transitional flows. Future directions of research in the field are outlined.

Spectral signature verification using statistical analysis and text mining

NASA Astrophysics Data System (ADS)

DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.

2016-05-01

In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is present for comparison. The spectral validation method proposed is described from a practical application and analytical perspective.

Spectral/ hp element methods: Recent developments, applications, and perspectives

NASA Astrophysics Data System (ADS)

Xu, Hui; Cantwell, Chris D.; Monteserin, Carlos; Eskilsson, Claes; Engsig-Karup, Allan P.; Sherwin, Spencer J.

2018-02-01

The spectral/ hp element method combines the geometric flexibility of the classical h-type finite element technique with the desirable numerical properties of spectral methods, employing high-degree piecewise polynomial basis functions on coarse finite element-type meshes. The spatial approximation is based upon orthogonal polynomials, such as Legendre or Chebychev polynomials, modified to accommodate a C 0 - continuous expansion. Computationally and theoretically, by increasing the polynomial order p, high-precision solutions and fast convergence can be obtained and, in particular, under certain regularity assumptions an exponential reduction in approximation error between numerical and exact solutions can be achieved. This method has now been applied in many simulation studies of both fundamental and practical engineering flows. This paper briefly describes the formulation of the spectral/ hp element method and provides an overview of its application to computational fluid dynamics. In particular, it focuses on the use of the spectral/ hp element method in transitional flows and ocean engineering. Finally, some of the major challenges to be overcome in order to use the spectral/ hp element method in more complex science and engineering applications are discussed.

Mobile micro-colorimeter and micro-spectrometer sensor modules as enablers for the replacement of subjective inspections by objective measurements for optically clear colored liquids in-field

NASA Astrophysics Data System (ADS)

Dittrich, Paul-Gerald; Grunert, Fred; Ehehalt, Jörg; Hofmann, Dietrich

2015-03-01

Aim of the paper is to show that the colorimetric characterization of optically clear colored liquids can be performed with different measurement methods and their application specific multichannel spectral sensors. The possible measurement methods are differentiated by the applied types of multichannel spectral sensors and therefore by their spectral resolution, measurement speed, measurement accuracy and measurement costs. The paper describes how different types of multichannel spectral sensors are calibrated with different types of calibration methods and how the measurement values can be used for further colorimetric calculations. The different measurement methods and the different application specific calibration methods will be explained methodically and theoretically. The paper proofs that and how different multichannel spectral sensor modules with different calibration methods can be applied with smartpads for the calculation of measurement results both in laboratory and in field. A given practical example is the application of different multichannel spectral sensors for the colorimetric characterization of petroleum oils and fuels and their colorimetric characterization by the Saybolt color scale.

Spectrum-based method to generate good decoy libraries for spectral library searching in peptide identifications.

PubMed

Cheng, Chia-Ying; Tsai, Chia-Feng; Chen, Yu-Ju; Sung, Ting-Yi; Hsu, Wen-Lian

2013-05-03

As spectral library searching has received increasing attention for peptide identification, constructing good decoy spectra from the target spectra is the key to correctly estimating the false discovery rate in searching against the concatenated target-decoy spectral library. Several methods have been proposed to construct decoy spectral libraries. Most of them construct decoy peptide sequences and then generate theoretical spectra accordingly. In this paper, we propose a method, called precursor-swap, which directly constructs decoy spectral libraries directly at the "spectrum level" without generating decoy peptide sequences by swapping the precursors of two spectra selected according to a very simple rule. Our spectrum-based method does not require additional efforts to deal with ion types (e.g., a, b or c ions), fragment mechanism (e.g., CID, or ETD), or unannotated peaks, but preserves many spectral properties. The precursor-swap method is evaluated on different spectral libraries and the results of obtained decoy ratios show that it is comparable to other methods. Notably, it is efficient in time and memory usage for constructing decoy libraries. A software tool called Precursor-Swap-Decoy-Generation (PSDG) is publicly available for download at http://ms.iis.sinica.edu.tw/PSDG/.

Robust and transferable quantification of NMR spectral quality using IROC analysis

NASA Astrophysics Data System (ADS)

Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.

2017-12-01

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

The analysis on the relation between the compression method and the performance enhancement of MSC (Multi-Spectral Camera) image data

NASA Astrophysics Data System (ADS)

Yong, Sang-Soon; Ra, Sung-Woong

2007-10-01

Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The instrument images the earth using a push-broom motion with a swath width of 15 km and a ground sample distance (GSD) of 1 m over the entire field of view (FOV) at altitude 685 Km. The instrument is designed to have an on-orbit operation duty cycle of 20% over the mission lifetime of 3 years with the functions of programmable gain/ offset and on-board image data compression/ storage. The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed, and the relation between both methods is to be analyzed and discussed.

Adaptive handling of Rayleigh and Raman scatter of fluorescence data based on evaluation of the degree of spectral overlap

NASA Astrophysics Data System (ADS)

Hu, Yingtian; Liu, Chao; Wang, Xiaoping; Zhao, Dongdong

2018-06-01

At present the general scatter handling methods are unsatisfactory when scatter and fluorescence seriously overlap in excitation emission matrix. In this study, an adaptive method for scatter handling of fluorescence data is proposed. Firstly, the Raman scatter was corrected by subtracting the baseline of deionized water which was collected in each experiment to adapt to the intensity fluctuations. Then, the degrees of spectral overlap between Rayleigh scatter and fluorescence were classified into three categories based on the distance between the spectral peaks. The corresponding algorithms, including setting to zero, fitting on single or both sides, were implemented after the evaluation of the degree of overlap for individual emission spectra. The proposed method minimized the number of fitting and interpolation processes, which reduced complexity, saved time, avoided overfitting, and most importantly assured the authenticity of data. Furthermore, the effectiveness of this procedure on the subsequent PARAFAC analysis was assessed and compared to Delaunay interpolation by conducting experiments with four typical organic chemicals and real water samples. Using this method, we conducted long-term monitoring of tap water and river water near a dyeing and printing plant. This method can be used for improving adaptability and accuracy in the scatter handling of fluorescence data.

Iodine absorption cells quality evaluation methods

NASA Astrophysics Data System (ADS)

Hrabina, Jan; Zucco, Massimo; Holá, Miroslava; Šarbort, Martin; Acef, Ouali; Du-Burck, Frédéric; Lazar, Josef; Číp, Ondřej

2016-12-01

The absorption cells represent an unique tool for the laser frequency stabilization. They serve as irreplaceable optical frequency references in realization of high-stable laser standards and laser sources for different brands of optical measurements, including the most precise frequency and dimensional measurement systems. One of the most often used absorption media covering visible and near IR spectral range is molecular iodine. It offers rich atlas of very strong and narrow spectral transitions which allow realization of laser systems with ultimate frequency stabilities in or below 10-14 order level. One of the most often disccussed disadvantage of the iodine cells is iodine's corrosivity and sensitivity to presence of foreign substances. The impurities react with absorption media and cause spectral shifts of absorption spectra, spectral broadening of the transitions and decrease achievable signal-to-noise ratio of the detected spectra. All of these unwanted effects directly influence frequency stability of the realized laser standard and due to this fact, the quality of iodine cells must be precisely controlled. We present a comparison of traditionally used method of laser induced fluorescence (LIF) with novel technique based on hyperfine transitions linewidths measurement. The results summarize advantages and drawbacks of these techniques and give a recommendation for their practical usage.

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.

Image-based spectral distortion correction for photon-counting x-ray detectors

PubMed Central

Ding, Huanjun; Molloi, Sabee

2012-01-01

Purpose: To investigate the feasibility of using an image-based method to correct for distortions induced by various artifacts in the x-ray spectrum recorded with photon-counting detectors for their application in breast computed tomography (CT). Methods: The polyenergetic incident spectrum was simulated with the tungsten anode spectral model using the interpolating polynomials (TASMIP) code and carefully calibrated to match the x-ray tube in this study. Experiments were performed on a Cadmium-Zinc-Telluride (CZT) photon-counting detector with five energy thresholds. Energy bins were adjusted to evenly distribute the recorded counts above the noise floor. BR12 phantoms of various thicknesses were used for calibration. A nonlinear function was selected to fit the count correlation between the simulated and the measured spectra in the calibration process. To evaluate the proposed spectral distortion correction method, an empirical fitting derived from the calibration process was applied on the raw images recorded for polymethyl methacrylate (PMMA) phantoms of 8.7, 48.8, and 100.0 mm. Both the corrected counts and the effective attenuation coefficient were compared to the simulated values for each of the five energy bins. The feasibility of applying the proposed method to quantitative material decomposition was tested using a dual-energy imaging technique with a three-material phantom that consisted of water, lipid, and protein. The performance of the spectral distortion correction method was quantified using the relative root-mean-square (RMS) error with respect to the expected values from simulations or areal analysis of the decomposition phantom. Results: The implementation of the proposed method reduced the relative RMS error of the output counts in the five energy bins with respect to the simulated incident counts from 23.0%, 33.0%, and 54.0% to 1.2%, 1.8%, and 7.7% for 8.7, 48.8, and 100.0 mm PMMA phantoms, respectively. The accuracy of the effective attenuation coefficient of PMMA estimate was also improved with the proposed spectral distortion correction. Finally, the relative RMS error of water, lipid, and protein decompositions in dual-energy imaging was significantly reduced from 53.4% to 6.8% after correction was applied. Conclusions: The study demonstrated that dramatic distortions in the recorded raw image yielded from a photon-counting detector could be expected, which presents great challenges for applying the quantitative material decomposition method in spectral CT. The proposed semi-empirical correction method can effectively reduce these errors caused by various artifacts, including pulse pileup and charge sharing effects. Furthermore, rather than detector-specific simulation packages, the method requires a relatively simple calibration process and knowledge about the incident spectrum. Therefore, it may be used as a generalized procedure for the spectral distortion correction of different photon-counting detectors in clinical breast CT systems. PMID:22482608

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.

Compressive Spectral Method for the Simulation of the Nonlinear Gravity Waves

PubMed Central

Bayındır, Cihan

2016-01-01

In this paper an approach for decreasing the computational effort required for the spectral simulations of the fully nonlinear ocean waves is introduced. The proposed approach utilizes the compressive sampling algorithm and depends on the idea of using a smaller number of spectral components compared to the classical spectral method. After performing the time integration with a smaller number of spectral components and using the compressive sampling technique, it is shown that the ocean wave field can be reconstructed with a significantly better efficiency compared to the classical spectral method. For the sparse ocean wave model in the frequency domain the fully nonlinear ocean waves with Jonswap spectrum is considered. By implementation of a high-order spectral method it is shown that the proposed methodology can simulate the linear and the fully nonlinear ocean waves with negligible difference in the accuracy and with a great efficiency by reducing the computation time significantly especially for large time evolutions. PMID:26911357

Calibrating Laser Gas Measurements by Use of Natural CO2

NASA Technical Reports Server (NTRS)

Webster, Chris

2003-01-01

An improved method of calibration has been devised for instruments that utilize tunable lasers to measure the absorption spectra of atmospheric gases in order to determine the relative abundances of the gases. In this method, CO2 in the atmosphere is used as a natural calibration standard. Unlike in one prior calibration method, it is not necessary to perform calibration measurements in advance of use of the instrument and to risk deterioration of accuracy with time during use. Unlike in another prior calibration method, it is not necessary to include a calibration gas standard (and the attendant additional hardware) in the instrument and to interrupt the acquisition of atmospheric data to perform calibration measurements. In the operation of an instrument of this type, the beam from a tunable diode laser or a tunable quantum-cascade laser is directed along a path through the atmosphere, the laser is made to scan in wavelength over an infrared spectral region that contains one or two absorption spectral lines of a gas of interest, and the transmission (and, thereby, the absorption) of the beam is measured. The concentration of the gas of interest can then be calculated from the observed depth of the absorption line(s), given the temperature, pressure, and path length. CO2 is nearly ideal as a natural calibration gas for the following reasons: CO2 has numerous rotation/vibration infrared spectral lines, many of which are near absorption lines of other gases. The concentration of CO2 relative to the concentrations of the major constituents of the atmosphere is well known and varies slowly and by a small enough amount to be considered constant for calibration in the present context. Hence, absorption-spectral measurements of the concentrations of gases of interest can be normalized to the concentrations of CO2. Because at least one CO2 calibration line is present in every spectral scan of the laser during absorption measurements, the atmospheric CO2 serves continuously as a calibration standard for every measurement point. Figure 1 depicts simulated spectral transmission measurements in a wavenumber range that contains two absorption lines of N2O and one of CO2. The simulations were performed for two different upper-atmospheric pressures for an airborne instrument that has a path length of 80 m. The relative abundance of CO2 in air was assumed to be 360 parts per million by volume (approximately its natural level in terrestrial air). In applying the present method to measurements like these, one could average the signals from the two N2O absorption lines and normalize their magnitudes to that of the CO2 absorption line. Other gases with which this calibration method can be used include H2O, CH4, CO, NO, NO2, HOCl, C2H2, NH3, O3, and HCN. One can also take advantage of this method to eliminate an atmospheric-pressure gauge and thereby reduce the mass of the instrument: The atmospheric pressure can be calculated from the temperature, the known relative abundance of CO2, and the concentration of CO2 as measured by spectral absorption. Natural CO2 levels on Mars provide an ideal calibration standard. Figure 2 shows a second example of the application of this method to Mars atmospheric gas measurements. For sticky gases like H2O, the method is particularly powerful, since water is notoriously difficult to handle at low concentrations in pre-flight calibration procedures.

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

Remote Sensing of Parasitic Nematodes in Plants

NASA Technical Reports Server (NTRS)

Lawrence, Gary W.; King, Roger; Kelley, Amber T.; Vickery, John

2007-01-01

A method and apparatus for remote sensing of parasitic nematodes in plants, now undergoing development, is based on measurement of visible and infrared spectral reflectances of fields where the plants are growing. Initial development efforts have been concentrated on detecting reniform nematodes (Rotylenchulus reniformis) in cotton plants, because of the economic importance of cotton crops. The apparatus includes a hand-held spectroradiometer. The readings taken by the radiometer are processed to extract spectral reflectances at sixteen wavelengths between 451 and 949 nm that, taken together, have been found to be indicative of the presence of Rotylenchulus reniformis. The intensities of the spectral reflectances are used to estimate the population density of the nematodes in an area from which readings were taken.

Spectral methods for partial differential equations

NASA Technical Reports Server (NTRS)

Hussaini, M. Y.; Streett, C. L.; Zang, T. A.

1983-01-01

Origins of spectral methods, especially their relation to the Method of Weighted Residuals, are surveyed. Basic Fourier, Chebyshev, and Legendre spectral concepts are reviewed, and demonstrated through application to simple model problems. Both collocation and tau methods are considered. These techniques are then applied to a number of difficult, nonlinear problems of hyperbolic, parabolic, elliptic, and mixed type. Fluid dynamical applications are emphasized.

Recent applications of spectral methods in fluid dynamics

NASA Technical Reports Server (NTRS)

Zang, T. A.; Hussaini, M. Y.

1985-01-01

Origins of spectral methods, especially their relation to the method of weighted residuals, are surveyed. Basic Fourier and Chebyshev spectral concepts are reviewed and demonstrated through application to simple model problems. Both collocation and tau methods are considered. These techniques are then applied to a number of difficult, nonlinear problems of hyperbolic, parabolic, elliptic and mixzed type. Fluid dynamical applications are emphasized.

An Improved Spectral Analysis Method for Fatigue Damage Assessment of Details in Liquid Cargo Tanks

NASA Astrophysics Data System (ADS)

Zhao, Peng-yuan; Huang, Xiao-ping

2018-03-01

Errors will be caused in calculating the fatigue damages of details in liquid cargo tanks by using the traditional spectral analysis method which is based on linear system, for the nonlinear relationship between the dynamic stress and the ship acceleration. An improved spectral analysis method for the assessment of the fatigue damage in detail of a liquid cargo tank is proposed in this paper. Based on assumptions that the wave process can be simulated by summing the sinusoidal waves in different frequencies and the stress process can be simulated by summing the stress processes induced by these sinusoidal waves, the stress power spectral density (PSD) is calculated by expanding the stress processes induced by the sinusoidal waves into Fourier series and adding the amplitudes of each harmonic component with the same frequency. This analysis method can take the nonlinear relationship into consideration and the fatigue damage is then calculated based on the PSD of stress. Take an independent tank in an LNG carrier for example, the accuracy of the improved spectral analysis method is proved much better than that of the traditional spectral analysis method by comparing the calculated damage results with the results calculated by the time domain method. The proposed spectral analysis method is more accurate in calculating the fatigue damages in detail of ship liquid cargo tanks.

Constrained spectral clustering under a local proximity structure assumption

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; Xu, Qianjun; des Jardins, Marie

2005-01-01

This work focuses on incorporating pairwise constraints into a spectral clustering algorithm. A new constrained spectral clustering method is proposed, as well as an active constraint acquisition technique and a heuristic for parameter selection. We demonstrate that our constrained spectral clustering method, CSC, works well when the data exhibits what we term local proximity structure.

Three-stage Fabry-Perot liquid crystal tunable filter with extended spectral range.

PubMed

Zheng, Zhenrong; Yang, Guowei; Li, Haifeng; Liu, Xu

2011-01-31

A method to extend spectral range of tunable optical filter is proposed in this paper. Two same tunable Fabry-Perot filters and an additional tunable filter with different free spectral range are cascaded to extend spectral range and reduce sidelobes. Over 400 nm of free spectral range and 4 nm of full width at half maximum of the filter were achieved. Design procedure and simulation are described in detail. An experimental 3-stage tunable Fabry-Perot filter with visible and infrared spectra is demonstrated. The experimental results and the theoretical analysis are presented in detail to verify this method. The results revealed that a compact and extended tunable spectral range of Fabry-Perot filter can be easily attainable by this method.

Estimation of Soil Moisture Content from the Spectral Reflectance of Bare Soils in the 0.4–2.5 μm Domain

PubMed Central

Fabre, Sophie; Briottet, Xavier; Lesaignoux, Audrey

2015-01-01

This work aims to compare the performance of new methods to estimate the Soil Moisture Content (SMC) of bare soils from their spectral signatures in the reflective domain (0.4–2.5 μm) in comparison with widely used spectral indices like Normalized Soil Moisture Index (NSMI) and Water Index SOIL (WISOIL). Indeed, these reference spectral indices use wavelengths located in the water vapour absorption bands and their performance are thus very sensitive to the quality of the atmospheric compensation. To reduce these limitations, two new spectral indices are proposed which wavelengths are defined using the determination matrix tool by taking into account the atmospheric transmission: Normalized Index of Nswir domain for Smc estimatiOn from Linear correlation (NINSOL) and Normalized Index of Nswir domain for Smc estimatiOn from Non linear correlation (NINSON). These spectral indices are completed by two new methods based on the global shape of the soil spectral signatures. These methods are the Inverse Soil semi-Empirical Reflectance model (ISER), using the inversion of an existing empirical soil model simulating the soil spectral reflectance according to soil moisture content for a given soil class, and the convex envelope model, linking the area between the envelope and the spectral signature to the SMC. All these methods are compared using a reference database built with 32 soil samples and composed of 190 spectral signatures with five or six soil moisture contents. Half of the database is used for the calibration stage and the remaining to evaluate the performance of the SMC estimation methods. The results show that the four new methods lead to similar or better performance than the one obtained by the reference indices. The RMSE is ranging from 3.8% to 6.2% and the coefficient of determination R2 varies between 0.74 and 0.91 with the best performance obtained with the ISER model. In a second step, simulated spectral radiances at the sensor level are used to analyse the sensitivity of these methods to the sensor spectral resolution and the water vapour content knowledge. The spectral signatures of the database are then used to simulate the signal at the top of atmosphere with a radiative transfer model and to compute the integrated incident signal representing the spectral radiance measurements of the HYMAP airborne hyperspectral instrument. The sensor radiances are then corrected from the atmosphere by an atmospheric compensation tool to retrieve the surface reflectances. The SMC estimation methods are then applied on the retrieve spectral reflectances. The adaptation of the spectral index wavelengths to the HyMap sensor spectral bands and the application of the convex envelope and ISER models to boarder spectral bands lead to an error on the SMC estimation. The best performance is then obtained with the ISER model (RMSE of 2.9% and R2 of 0.96) while the four other methods lead to quite similar RMSE (from 6.4% to 7.8%) and R2 (between 0.79 and 0.83) values. In the atmosphere compensation processing, an error on the water vapour content is introduced. The most robust methods to water vapour content variations are WISOIL, NINSON, NINSOL and ISER model. The convex envelope model and NSMI index require an accurate estimation of the water vapour content in the atmosphere. PMID:25648710

Two-Flux Green's Function Analysis for Transient Spectral Radiation in a Composite

NASA Technical Reports Server (NTRS)

Siegel, Robert

1996-01-01

An analysis is developed for obtaining transient temperatures in a two-layer semitransparent composite with spectrally dependent properties. Each external boundary of the composite is subjected to radiation and convection. The two-flux radiative transfer equations are solved by deriving a Green's function. This yields the local radiative heat source needed to numerically solve the transient energy equation. An advantage of the two-flux method is that isotropic scattering is included without added complexity. The layer refractive indices are larger than one. This produces internal reflections at the boundaries and the internal interface; the reflections are assumed diffuse. Spectral results using the Green's function method are verified by comparing with numerical solutions using the exact radiative transfer equations. Transient temperature distributions are given to illustrate the effect of radiative heating on one side of a composite with external convective cooling. The protection of a material from incident radiation is illustrated by adding scattering to the layer adjacent to the radiative source.

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.

Development of Translational Methods in Spectral Analysis of Human Infant Crying and Rat Pup Ultrasonic Vocalizations for Early Neurobehavioral Assessment

PubMed Central

Zeskind, Philip Sanford; McMurray, Matthew S.; Garber, Kristin A.; Neuspiel, Juliana M.; Cox, Elizabeth T.; Grewen, Karen M.; Mayes, Linda C.; Johns, Josephine M.

2011-01-01

The purpose of this article is to describe the development of translational methods by which spectrum analysis of human infant crying and rat pup ultrasonic vocalizations (USVs) can be used to assess potentially adverse effects of various prenatal conditions on early neurobehavioral development. The study of human infant crying has resulted in a rich set of measures that has long been used to assess early neurobehavioral insult due to non-optimal prenatal environments, even among seemingly healthy newborn and young infants. In another domain of study, the analysis of rat put USVs has been conducted via paradigms that allow for better experimental control over correlated prenatal conditions that may confound findings and conclusions regarding the effects of specific prenatal experiences. The development of translational methods by which cry vocalizations of both species can be analyzed may provide the opportunity for findings from the two approaches of inquiry to inform one another through their respective strengths. To this end, we present an enhanced taxonomy of a novel set of common measures of cry vocalizations of both human infants and rat pups based on a conceptual framework that emphasizes infant crying as a graded and dynamic acoustic signal. This set includes latency to vocalization onset, duration and repetition rate of expiratory components, duration of inter-vocalization-intervals and spectral features of the sound, including the frequency and amplitude of the fundamental and dominant frequencies. We also present a new set of classifications of rat pup USV waveforms that include qualitative shifts in fundamental frequency, similar to the presence of qualitative shifts in fundamental frequency that have previously been related to insults to neurobehavioral integrity in human infants. Challenges to the development of translational analyses, including the use of different terminologies, methods of recording, and spectral analyses are discussed, as well as descriptions of automated processes, software solutions, and pitfalls. PMID:22028695

Frequency-Domain Identification Of Aeroelastic Modes

NASA Technical Reports Server (NTRS)

Acree, C. W., Jr.; Tischler, Mark B.

1991-01-01

Report describes flight measurements and frequency-domain analyses of aeroelastic vibrational modes of wings of XV-15 tilt-rotor aircraft. Begins with description of flight-test methods. Followed by brief discussion of methods of analysis, which include Fourier-transform computations using chirp z transformers, use of coherence and other spectral functions, and methods and computer programs to obtain frequencies and damping coefficients from measurements. Includes brief description of results of flight tests and comparisions among various experimental and theoretical results. Ends with section on conclusions and recommended improvements in techniques.

An evaluation of random analysis methods for the determination of panel damping

NASA Technical Reports Server (NTRS)

Bhat, W. V.; Wilby, J. F.

1972-01-01

An analysis is made of steady-state and non-steady-state methods for the measurement of panel damping. Particular emphasis is placed on the use of random process techniques in conjunction with digital data reduction methods. The steady-state methods considered use the response power spectral density, response autocorrelation, excitation-response crosspower spectral density, or single-sided Fourier transform (SSFT) of the response autocorrelation function. Non-steady-state methods are associated mainly with the use of rapid frequency sweep excitation. Problems associated with the practical application of each method are evaluated with specific reference to the case of a panel exposed to a turbulent airflow, and two methods, the power spectral density and the single-sided Fourier transform methods, are selected as being the most suitable. These two methods are demonstrated experimentally, and it is shown that the power spectral density method is satisfactory under most conditions, provided that appropriate corrections are applied to account for filter bandwidth and background noise errors. Thus, the response power spectral density method is recommended for the measurement of the damping of panels exposed to a moving airflow.

A novel edge-preserving nonnegative matrix factorization method for spectral unmixing

NASA Astrophysics Data System (ADS)

Bao, Wenxing; Ma, Ruishi

2015-12-01

Spectral unmixing technique is one of the key techniques to identify and classify the material in the hyperspectral image processing. A novel robust spectral unmixing method based on nonnegative matrix factorization(NMF) is presented in this paper. This paper used an edge-preserving function as hypersurface cost function to minimize the nonnegative matrix factorization. To minimize the hypersurface cost function, we constructed the updating functions for signature matrix of end-members and abundance fraction respectively. The two functions are updated alternatively. For evaluation purpose, synthetic data and real data have been used in this paper. Synthetic data is used based on end-members from USGS digital spectral library. AVIRIS Cuprite dataset have been used as real data. The spectral angle distance (SAD) and abundance angle distance(AAD) have been used in this research for assessment the performance of proposed method. The experimental results show that this method can obtain more ideal results and good accuracy for spectral unmixing than present methods.

A Legendre tau-spectral method for solving time-fractional heat equation with nonlocal conditions.

PubMed

Bhrawy, A H; Alghamdi, M A

2014-01-01

We develop the tau-spectral method to solve the time-fractional heat equation (T-FHE) with nonlocal condition. In order to achieve highly accurate solution of this problem, the operational matrix of fractional integration (described in the Riemann-Liouville sense) for shifted Legendre polynomials is investigated in conjunction with tau-spectral scheme and the Legendre operational polynomials are used as the base function. The main advantage in using the presented scheme is that it converts the T-FHE with nonlocal condition to a system of algebraic equations that simplifies the problem. For demonstrating the validity and applicability of the developed spectral scheme, two numerical examples are presented. The logarithmic graphs of the maximum absolute errors is presented to achieve the exponential convergence of the proposed method. Comparing between our spectral method and other methods ensures that our method is more accurate than those solved similar problem.

A Legendre tau-Spectral Method for Solving Time-Fractional Heat Equation with Nonlocal Conditions

PubMed Central

Bhrawy, A. H.; Alghamdi, M. A.

2014-01-01

We develop the tau-spectral method to solve the time-fractional heat equation (T-FHE) with nonlocal condition. In order to achieve highly accurate solution of this problem, the operational matrix of fractional integration (described in the Riemann-Liouville sense) for shifted Legendre polynomials is investigated in conjunction with tau-spectral scheme and the Legendre operational polynomials are used as the base function. The main advantage in using the presented scheme is that it converts the T-FHE with nonlocal condition to a system of algebraic equations that simplifies the problem. For demonstrating the validity and applicability of the developed spectral scheme, two numerical examples are presented. The logarithmic graphs of the maximum absolute errors is presented to achieve the exponential convergence of the proposed method. Comparing between our spectral method and other methods ensures that our method is more accurate than those solved similar problem. PMID:25057507

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.

Numerical solution of the quantum Lenard-Balescu equation for a non-degenerate one-component plasma

DOE PAGES

Scullard, Christian R.; Belt, Andrew P.; Fennell, Susan C.; ...

2016-09-01

We present a numerical solution of the quantum Lenard-Balescu equation using a spectral method, namely an expansion in Laguerre polynomials. This method exactly conserves both particles and kinetic energy and facilitates the integration over the dielectric function. To demonstrate the method, we solve the equilibration problem for a spatially homogeneous one-component plasma with various initial conditions. Unlike the more usual Landau/Fokker-Planck system, this method requires no input Coulomb logarithm; the logarithmic terms in the collision integral arise naturally from the equation along with the non-logarithmic order-unity terms. The spectral method can also be used to solve the Landau equation andmore » a quantum version of the Landau equation in which the integration over the wavenumber requires only a lower cutoff. We solve these problems as well and compare them with the full Lenard-Balescu solution in the weak-coupling limit. Finally, we discuss the possible generalization of this method to include spatial inhomogeneity and velocity anisotropy.« less

Nonconforming mortar element methods: Application to spectral discretizations

NASA Technical Reports Server (NTRS)

Maday, Yvon; Mavriplis, Cathy; Patera, Anthony

1988-01-01

Spectral element methods are p-type weighted residual techniques for partial differential equations that combine the generality of finite element methods with the accuracy of spectral methods. Presented here is a new nonconforming discretization which greatly improves the flexibility of the spectral element approach as regards automatic mesh generation and non-propagating local mesh refinement. The method is based on the introduction of an auxiliary mortar trace space, and constitutes a new approach to discretization-driven domain decomposition characterized by a clean decoupling of the local, structure-preserving residual evaluations and the transmission of boundary and continuity conditions. The flexibility of the mortar method is illustrated by several nonconforming adaptive Navier-Stokes calculations in complex geometry.

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.

Vibrational spectral signatures of crystalline cellulose using high resolution broadband sum frequency generation vibrational spectroscopy (HR-BB-SFG-VS)

DOE PAGES

Zhang, Libing; Lu, Zhou; Velarde, Luis; ...

2015-03-03

Both the C–H and O–H region spectra of crystalline cellulose were studied using the sub-wavenumber high-resolution broadband sum frequency generation vibrational spectroscopy (HR-BB-SFG-VS) for the first time. The resolution of HR-BB-SFG-VS is about 10-times better than conventional scanning SFG-VS and has the capability of measuring the intrinsic spectral lineshape and revealing many more spectral details. With HR-BB-SFG-VS, we found that in cellulose samples from different sources, including Avicel and cellulose crystals isolated from algae Valonia (Iα) and tunicates (Iβ), the spectral signatures in the O–H region were unique for the two allomorphs, i.e. Iα and Iβ, while the spectral signaturesmore » in the C–H regions varied in all samples examined. Even though the origin of the different spectral signatures of the crystalline cellulose in the O–H and C–H vibrational frequency regions are yet to be correlated to the structure of cellulose, these results lead to new spectroscopic methods and opportunities to classify and to understand the basic crystalline structures, as well as variations in polymorphism of the crystalline cellulose.« less

Vibrational spectral signatures of crystalline cellulose using high resolution broadband sum frequency generation vibrational spectroscopy (HR-BB-SFG-VS)

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

Zhang, Libing; Lu, Zhou; Velarde, Luis

Both the C–H and O–H region spectra of crystalline cellulose were studied using the sub-wavenumber high-resolution broadband sum frequency generation vibrational spectroscopy (HR-BB-SFG-VS) for the first time. The resolution of HR-BB-SFG-VS is about 10-times better than conventional scanning SFG-VS and has the capability of measuring the intrinsic spectral lineshape and revealing many more spectral details. With HR-BB-SFG-VS, we found that in cellulose samples from different sources, including Avicel and cellulose crystals isolated from algae Valonia (Iα) and tunicates (Iβ), the spectral signatures in the O–H region were unique for the two allomorphs, i.e. Iα and Iβ, while the spectral signaturesmore » in the C–H regions varied in all samples examined. Even though the origin of the different spectral signatures of the crystalline cellulose in the O–H and C–H vibrational frequency regions are yet to be correlated to the structure of cellulose, these results lead to new spectroscopic methods and opportunities to classify and to understand the basic crystalline structures, as well as variations in polymorphism of the crystalline cellulose.« less

Different techniques of multispectral data analysis for vegetation fraction retrieval

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2012-07-01

Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

[Study of the Detecting System of CH4 and SO2 Based on Spectral Absorption Method and UV Fluorescence Method].

PubMed

Wang, Shu-tao; Wang, Zhi-fang; Liu, Ming-hua; Wei, Meng; Chen, Dong-ying; Wang, Xing-long

2016-01-01

According to the spectral absorption characteristics of polluting gases and fluorescence characteristics, a time-division multiplexing detection system is designed. Through this system we can detect Methane (CH4) and sulfur dioxide (SO2) by using spectral absorption method and the SO2 can be detected by using UV fluorescence method. The system consists of four parts: a combination of a light source which could be switched, the common optical path, the air chamber and the signal processing section. The spectral absorption characteristics and fluorescence characteristics are measured first. Then the experiment of detecting CH4 and SO2 through spectral absorption method and the experiment of detecting SO2 through UV fluorescence method are conducted, respectively. Through measuring characteristics of spectral absorption and fluorescence, we get excitation wavelengths of SO2 and CH4 measured by spectral absorption method at the absorption peak are 280 nm and 1.64 μm, respectively, and the optimal excitation wavelength of SO2 measured by UV fluorescence method is 220 nm. we acquire the linear relation between the concentration of CH4 and relative intensity and the linear relation between the concentration of SO2 and output voltage after conducting the experiment of spectral absorption method, and the linearity are 98.7%, 99.2% respectively. Through the experiment of UV fluorescence method we acquire that the relation between the concentration of SO2 and the voltage is linear, and the linearity is 99.5%. Research shows that the system is able to be applied to detect the polluted gas by absorption spectrum method and UV fluorescence method. Combing these two measurement methods decreases the costing and the volume, and this system can also be used to measure the other gases. Such system has a certain value of application.

Review on SERS of Bacteria

PubMed Central

Mosier-Boss, Pamela A.

2017-01-01

Surface enhanced Raman spectroscopy (SERS) has been widely used for chemical detection. Moreover, the inherent richness of the spectral data has made SERS attractive for use in detecting biological materials, including bacteria. This review discusses methods that have been used to obtain SERS spectra of bacteria. The kinds of SERS substrates employed to obtain SERS spectra are discussed as well as how bacteria interact with silver and gold nanoparticles. The roll of capping agents on Ag/Au NPs in obtaining SERS spectra is examined as well as the interpretation of the spectral data. PMID:29137201

Exploiting physical constraints for multi-spectral exo-planet detection

NASA Astrophysics Data System (ADS)

Thiébaut, Éric; Devaney, Nicholas; Langlois, Maud; Hanley, Kenneth

2016-07-01

We derive a physical model of the on-axis PSF for a high contrast imaging system such as GPI or SPHERE. This model is based on a multi-spectral Taylor series expansion of the diffraction pattern and predicts that the speckles should be a combination of spatial modes with deterministic chromatic magnification and weighting. We propose to remove most of the residuals by fitting this model on a set of images at multiple wavelengths and times. On simulated data, we demonstrate that our approach achieves very good speckle suppression without additional heuristic parameters. The residual speckles1, 2 set the most serious limitation in the detection of exo-planets in high contrast coronographic images provided by instruments such as SPHERE3 at the VLT, GPI4, 5 at Gemini, or SCExAO6 at Subaru. A number of post-processing methods have been proposed to remove as much as possible of the residual speckles while preserving the signal from the planets. These methods exploit the fact that the speckles and the planetary signal have different temporal and spectral behaviors. Some methods like LOCI7 are based on angular differential imaging8 (ADI), spectral differential imaging9, 10 (SDI), or on a combination of ADI and SDI.11 Instead of working on image differences, we propose to tackle the exo-planet detection as an inverse problem where a model of the residual speckles is fit on the set of multi-spectral images and, possibly, multiple exposures. In order to reduce the number of degrees of freedom, we impose specific constraints on the spatio-spectral distribution of stellar speckles. These constraints are deduced from a multi-spectral Taylor series expansion of the diffraction pattern for an on-axis source which implies that the speckles are a combination of spatial modes with deterministic chromatic magnification and weighting. Using simulated data, the efficiency of speckle removal by fitting the proposed multi-spectral model is compared to the result of using an approximation based on the singular value decomposition of the rescaled images. We show how the difficult problem to fitting a bilinear model on the can be solved in practise. The results are promising for further developments including application to real data and joint planet detection in multi-variate data (multi-spectral and multiple exposures images).

Possibility of successive SRXFA use along with chemical-spectral methods for palladium analysis in geological samples

NASA Astrophysics Data System (ADS)

Kislov, E. V.; Kulikov, A. A.; Kulikova, A. B.

1989-10-01

Samples of basit-ultrabasit rocks and NiCu ores of the Ioko-Dovyren and Chaya massifs were analysed by SRXFA and a chemical-spectral method. SRXFA perfectly satisfies the quantitative noble-metals analysis of ore-free rocks. Combination of SRXFA and chemical-spectral analysis has good prospects. After analysis of a great number of samples by SRXFA it is necessary to select samples which would show minimal and maximal results for the chemical-spectral method.

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.

Bulk mineralogy of the NE Syrtis and Jezero crater regions of Mars derived through thermal infrared spectral analyses

NASA Astrophysics Data System (ADS)

Salvatore, M. R.; Goudge, T. A.; Bramble, M. S.; Edwards, C. S.; Bandfield, J. L.; Amador, E. S.; Mustard, J. F.; Christensen, P. R.

2018-02-01

We investigated the area to the northwest of the Isidis impact basin (hereby referred to as "NW Isidis") using thermal infrared emission datasets to characterize and quantify bulk surface mineralogy throughout this region. This area is home to Jezero crater and the watershed associated with its two deltaic deposits in addition to NE Syrtis and the strong and diverse visible/near-infrared spectral signatures observed in well-exposed stratigraphic sections. The spectral signatures throughout this region show a diversity of primary and secondary surface mineralogies, including olivine, pyroxene, smectite clays, sulfates, and carbonates. While previous thermal infrared investigations have sought to characterize individual mineral groups within this region, none have systematically assessed bulk surface mineralogy and related these observations to visible/near-infrared studies. We utilize an iterative spectral unmixing method to statistically evaluate our linear thermal infrared spectral unmixing models to derive surface mineralogy. All relevant primary and secondary phases identified in visible/near-infrared studies are included in the unmixing models and their modeled spectral contributions are discussed in detail. While the stratigraphy and compositional diversity observed in visible/near-infrared spectra are much better exposed and more diverse than most other regions of Mars, our thermal infrared analyses suggest the dominance of basaltic compositions with less observed variability in the amount and diversity of alteration phases. These results help to constrain the mineralogical context of these previously reported visible/near-infrared spectral identifications. The results are also discussed in the context of future in situ investigations, as the NW Isidis region has long been promoted as a region of paleoenvironmental interest on Mars.

Relative spectral response calibration using Ti plasma lines

NASA Astrophysics Data System (ADS)

Teng, FEI; Congyuan, PAN; Qiang, ZENG; Qiuping, WANG; Xuewei, DU

2018-04-01

This work introduces the branching ratio (BR) method for determining relative spectral responses, which are needed routinely in laser induced breakdown spectroscopy (LIBS). Neutral and singly ionized Ti lines in the 250–498 nm spectral range are investigated by measuring laser-induced micro plasma near a Ti plate and used to calculate the relative spectral response of an entire LIBS detection system. The results are compared with those of the conventional relative spectral response calibration method using a tungsten halogen lamp, and certain lines available for the BR method are selected. The study supports the common manner of using BRs to calibrate the detection system in LIBS setups.

Modified Spectral Fatigue Methods for S-N Curves With MIL-HDBK-5J Coefficients

NASA Technical Reports Server (NTRS)

Irvine, Tom; Larsen, Curtis

2016-01-01

The rainflow method is used for counting fatigue cycles from a stress response time history, where the fatigue cycles are stress-reversals. The rainflow method allows the application of Palmgren-Miner's rule in order to assess the fatigue life of a structure subject to complex loading. The fatigue damage may also be calculated from a stress response power spectral density (PSD) using the semi-empirical Dirlik, Single Moment, Zhao-Baker and other spectral methods. These methods effectively assume that the PSD has a corresponding time history which is stationary with a normal distribution. This paper shows how the probability density function for rainflow stress cycles can be extracted from each of the spectral methods. This extraction allows for the application of the MIL-HDBK-5J fatigue coefficients in the cumulative damage summation. A numerical example is given in this paper for the stress response of a beam undergoing random base excitation, where the excitation is applied separately by a time history and by its corresponding PSD. The fatigue calculation is performed in the time domain, as well as in the frequency domain via the modified spectral methods. The result comparison shows that the modified spectral methods give comparable results to the time domain rainflow counting method.

DNS of Flow in a Low-Pressure Turbine Cascade Using a Discontinuous-Galerkin Spectral-Element Method

NASA Technical Reports Server (NTRS)

Garai, Anirban; Diosady, Laslo Tibor; Murman, Scott; Madavan, Nateri

2015-01-01

A new computational capability under development for accurate and efficient high-fidelity direct numerical simulation (DNS) and large eddy simulation (LES) of turbomachinery is described. This capability is based on an entropy-stable Discontinuous-Galerkin spectral-element approach that extends to arbitrarily high orders of spatial and temporal accuracy and is implemented in a computationally efficient manner on a modern high performance computer architecture. A validation study using this method to perform DNS of flow in a low-pressure turbine airfoil cascade are presented. Preliminary results indicate that the method captures the main features of the flow. Discrepancies between the predicted results and the experiments are likely due to the effects of freestream turbulence not being included in the simulation and will be addressed in the final paper.

Nanophotonic Image Sensors.

PubMed

Chen, Qin; Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R S

2016-09-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial-based THz image sensors, filter-free nanowire image sensors and nanostructured-based multispectral image sensors. This novel combination of cutting edge photonics research and well-developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

An iterative approach for compound detection in an unknown pharmaceutical drug product: Application on Raman microscopy.

PubMed

Boiret, Mathieu; Gorretta, Nathalie; Ginot, Yves-Michel; Roger, Jean-Michel

2016-02-20

Raman chemical imaging provides both spectral and spatial information on a pharmaceutical drug product. Even if the main objective of chemical imaging is to obtain distribution maps of each formulation compound, identification of pure signals in a mixture dataset remains of huge interest. In this work, an iterative approach is proposed to identify the compounds in a pharmaceutical drug product, assuming that the chemical composition of the product is not known by the analyst and that a low dose compound can be present in the studied medicine. The proposed approach uses a spectral library, spectral distances and orthogonal projections to iteratively detect pure compounds of a tablet. Since the proposed method is not based on variance decomposition, it should be well adapted for a drug product which contains a low dose product, interpreted as a compound located in few pixels and with low spectral contributions. The method is tested on a tablet specifically manufactured for this study with one active pharmaceutical ingredient and five excipients. A spectral library, constituted of 24 pure pharmaceutical compounds, is used as a reference spectral database. Pure spectra of active and excipients, including a modification of the crystalline form and a low dose compound, are iteratively detected. Once the pure spectra are identified, multivariate curve resolution-alternating least squares process is performed on the data to provide distribution maps of each compound in the studied sample. Distributions of the two crystalline forms of active and the five excipients were in accordance with the theoretical formulation. Copyright © 2015 Elsevier B.V. All rights reserved.

De-Aliasing Through Over-Integration Applied to the Flux Reconstruction and Discontinuous Galerkin Methods

NASA Technical Reports Server (NTRS)

Spiegel, Seth C.; Huynh, H. T.; DeBonis, James R.

2015-01-01

High-order methods are quickly becoming popular for turbulent flows as the amount of computer processing power increases. The flux reconstruction (FR) method presents a unifying framework for a wide class of high-order methods including discontinuous Galerkin (DG), Spectral Difference (SD), and Spectral Volume (SV). It offers a simple, efficient, and easy way to implement nodal-based methods that are derived via the differential form of the governing equations. Whereas high-order methods have enjoyed recent success, they have been known to introduce numerical instabilities due to polynomial aliasing when applied to under-resolved nonlinear problems. Aliasing errors have been extensively studied in reference to DG methods; however, their study regarding FR methods has mostly been limited to the selection of the nodal points used within each cell. Here, we extend some of the de-aliasing techniques used for DG methods, primarily over-integration, to the FR framework. Our results show that over-integration does remove aliasing errors but may not remove all instabilities caused by insufficient resolution (for FR as well as DG).

The CFL condition for spectral approximations to hyperbolic initial-boundary value problems

NASA Technical Reports Server (NTRS)

Gottlieb, David; Tadmor, Eitan

1991-01-01

The stability of spectral approximations to scalar hyperbolic initial-boundary value problems with variable coefficients are studied. Time is discretized by explicit multi-level or Runge-Kutta methods of order less than or equal to 3 (forward Euler time differencing is included), and spatial discretizations are studied by spectral and pseudospectral approximations associated with the general family of Jacobi polynomials. It is proved that these fully explicit spectral approximations are stable provided their time-step, delta t, is restricted by the CFL-like condition, delta t less than Const. N(exp-2), where N equals the spatial number of degrees of freedom. We give two independent proofs of this result, depending on two different choices of approximate L(exp 2)-weighted norms. In both approaches, the proofs hinge on a certain inverse inequality interesting for its own sake. The result confirms the commonly held belief that the above CFL stability restriction, which is extensively used in practical implementations, guarantees the stability (and hence the convergence) of fully-explicit spectral approximations in the nonperiodic case.

The CFL condition for spectral approximations to hyperbolic initial-boundary value problems

NASA Technical Reports Server (NTRS)

Gottlieb, David; Tadmor, Eitan

1990-01-01

The stability of spectral approximations to scalar hyperbolic initial-boundary value problems with variable coefficients are studied. Time is discretized by explicit multi-level or Runge-Kutta methods of order less than or equal to 3 (forward Euler time differencing is included), and spatial discretizations are studied by spectral and pseudospectral approximations associated with the general family of Jacobi polynomials. It is proved that these fully explicit spectral approximations are stable provided their time-step, delta t, is restricted by the CFL-like condition, delta t less than Const. N(exp-2), where N equals the spatial number of degrees of freedom. We give two independent proofs of this result, depending on two different choices of approximate L(exp 2)-weighted norms. In both approaches, the proofs hinge on a certain inverse inequality interesting for its own sake. The result confirms the commonly held belief that the above CFL stability restriction, which is extensively used in practical implementations, guarantees the stability (and hence the convergence) of fully-explicit spectral approximations in the nonperiodic case.

Extracting spectral contrast in Landsat Thematic Mapper image data using selective principal component analysis

USGS Publications Warehouse

Chavez, P.S.; Kwarteng, A.Y.

1989-01-01

A challenge encountered with Landsat Thematic Mapper (TM) data, which includes data from size reflective spectral bands, is displaying as much information as possible in a three-image set for color compositing or digital analysis. Principal component analysis (PCA) applied to the six TM bands simultaneously is often used to address this problem. However, two problems that can be encountered using the PCA method are that information of interest might be mathematically mapped to one of the unused components and that a color composite can be difficult to interpret. "Selective' PCA can be used to minimize both of these problems. The spectral contrast among several spectral regions was mapped for a northern Arizona site using Landsat TM data. Field investigations determined that most of the spectral contrast seen in this area was due to one of the following: the amount of iron and hematite in the soils and rocks, vegetation differences, standing and running water, or the presence of gypsum, which has a higher moisture retention capability than do the surrounding soils and rocks. -from Authors

Spectral ratio method for measuring emissivity

USGS Publications Warehouse

Watson, K.

1992-01-01

The spectral ratio method is based on the concept that although the spectral radiances are very sensitive to small changes in temperature the ratios are not. Only an approximate estimate of temperature is required thus, for example, we can determine the emissivity ratio to an accuracy of 1% with a temperature estimate that is only accurate to 12.5 K. Selecting the maximum value of the channel brightness temperatures is an unbiased estimate. Laboratory and field spectral data are easily converted into spectral ratio plots. The ratio method is limited by system signal:noise and spectral band-width. The images can appear quite noisy because ratios enhance high frequencies and may require spatial filtering. Atmospheric effects tend to rescale the ratios and require using an atmospheric model or a calibration site. ?? 1992.

Special nuclear material simulation device

DOEpatents

Leckey, John H.; DeMint, Amy; Gooch, Jack; Hawk, Todd; Pickett, Chris A.; Blessinger, Chris; York, Robbie L.

2014-08-12

An apparatus for simulating special nuclear material is provided. The apparatus typically contains a small quantity of special nuclear material (SNM) in a configuration that simulates a much larger quantity of SNM. Generally the apparatus includes a spherical shell that is formed from an alloy containing a small quantity of highly enriched uranium. Also typically provided is a core of depleted uranium. A spacer, typically aluminum, may be used to separate the depleted uranium from the shell of uranium alloy. A cladding, typically made of titanium, is provided to seal the source. Methods are provided to simulate SNM for testing radiation monitoring portals. Typically the methods use at least one primary SNM spectral line and exclude at least one secondary SNM spectral line.

Nanotunneling Junction-based Hyperspectal Polarimetric Photodetector and Detection Method

NASA Technical Reports Server (NTRS)

Son, Kyung-ah (Inventor); Moon, Jeongsun J. (Inventor); Chattopadhyay, Goutam (Inventor); Liao, Anna (Inventor); Ting, David (Inventor)

2009-01-01

A photodetector, detector array, and method of operation thereof in which nanojunctions are formed by crossing layers of nanowires. The crossing nanowires are separated by a few nm thick electrical barrier layer which allows tunneling. Each nanojunction is coupled to a slot antenna for efficient and frequency-selective coupling to photo signals. The nanojunctions formed at the intersection of the crossing wires defines a vertical tunneling diode that rectifies the AC signal from a coupled antenna and generates a DC signal suitable for reforming a video image. The nanojunction sensor allows multi/hyper spectral imaging of radiation within a spectral band ranging from terahertz to visible light, and including infrared (IR) radiation. This new detection approach also offers unprecedented speed, sensitivity and fidelity at room temperature.

Simulation of time-dispersion spectral device with sample spectra accumulation

NASA Astrophysics Data System (ADS)

Zhdanov, Arseny; Khansuvarov, Ruslan; Korol, Georgy

2014-09-01

This research is conducted in order to design a spectral device for light sources power spectrum analysis. The spectral device should process radiation from sources, direct contact with radiation of which is either impossible or undesirable. Such sources include jet blast of an aircraft, optical radiation in metallurgy and textile industry. In proposed spectral device optical radiation is guided out of unfavorable environment via a piece of optical fiber with high dispersion. It is necessary for analysis to make samples of analyzed radiation as short pulses. Dispersion properties of such optical fiber cause spectral decomposition of input optical pulses. The faster time of group delay vary the stronger the spectral decomposition effect. This effect allows using optical fiber with high dispersion as a major element of proposed spectral device. Duration of sample must be much shorter than group delay time difference of a dispersive system. In the given frequency range this characteristic has to be linear. The frequency range is 400 … 500 THz for typical optical fiber. Using photonic-crystal fiber (PCF) gives much wider spectral range for analysis. In this paper we propose simulation of single pulse transmission through dispersive system with linear dispersion characteristic and quadratic-detected output responses accumulation. During simulation we propose studying influence of optical fiber dispersion characteristic angle on spectral measurement results. We also consider pulse duration and group delay time difference impact on output pulse shape and duration. Results show the most suitable dispersion characteristic that allow choosing the structure of PCF - major element of time-dispersion spectral analysis method and required number of samples for reliable assessment of measured spectrum.

Vegetation Red-edge Spectral Modeling for Solar-induced Chlorophyll Fluorescence Retrieval at O2-B Band

NASA Astrophysics Data System (ADS)

Huang, C.; Zhang, L.; Qiao, N.; Zhang, X.; Li, Y.

2015-12-01

Remotely sensed solar-induced chlorophyll fluorescence (SIF) has been considered an ideal probe in monitoring global vegetation photosynthesis. However, challenges in accurate estimate of faint SIF (less than 5% of the total reflected radiation in near infrared bands) from the observed apparent reflected radiation greatly limit its wide applications. Currently, the telluric O2-B (~688nm) and O2-A (~761nm) have been proved to be capable of SIF retrieval based on Fraunhofer line depth (FLD) principle. They may still work well even using conventional ground-based commercial spectrometers with typical spectral resolutions of 2~5 nm and high enough signal-to-noise ratio (e.g., the ASD spectrometer). Nevertheless, almost all current FLD based algorithms were mainly developed for O2-A, a few concentrating on the other SIF emission peak in O2-B. One of the critical reasons is that it is very difficult to model the sudden varying reflectance around O2-B band located in the red-edge spectral region (about 680-800 nm). This study investigates a new method by combining the established inverted Gaussian reflectance model (IGM) and FLD principle using diurnal canopy spectra with relative low spectral resolutions of 1 nm (FluorMOD simulations) and 3 nm (measured by ASD spectrometer) respectively. The IGM has been reported to be an objective and good method to characterize the entire vegetation red-edge reflectance. Consequently, the proposed SIF retrieval method (hereinafter called IGMFLD) could exploit all the spectral information along the whole red-edge (680-800 nm) to obtain more reasonable reflectance and fluorescence correction coefficients than traditional FLD methods such as the iFLD. Initial results show that the IGMFLD can better capture the spectrally non-linear characterization of the reflectance in 680-800 nm and thereby yields much more accurate SIFs in O2-B than typical FLD methods, including sFLD, 3FLD and iFLD (see figure 1). Finally, uncertainties and prospect of the IGM-FLD, in contrast with sFLD, 3FLD and iFLD, were discussed here. This study may provide a test-bed for developing more robust methods to retrieve SIF in O2-B from aircraft (e.g. AisaIBIS fluorescence imager) or satellite (FLEX-FLORIS) remote sensing measurements.

Laser systems configured to output a spectrally-consolidated laser beam and related methods

DOEpatents

Koplow, Jeffrey P [San Ramon, CA

2012-01-10

A laser apparatus includes a plurality of pumps each of which is configured to emit a corresponding pump laser beam having a unique peak wavelength. The laser apparatus includes a spectral beam combiner configured to combine the corresponding pump laser beams into a substantially spatially-coherent pump laser beam having a pump spectrum that includes the unique peak wavelengths, and first and second selectively reflective elements spaced from each other to define a lasing cavity including a lasing medium therein. The lasing medium generates a plurality of gain spectra responsive to absorbing the pump laser beam. Each gain spectrum corresponds to a respective one of the unique peak wavelengths of the substantially spatially-coherent pump laser beam and partially overlaps with all other ones of the gain spectra. The reflective elements are configured to promote emission of a laser beam from the lasing medium with a peak wavelength common to each gain spectrum.

Modeling ocean primary production: Sensitivity to spectral resolution of attenuation and absorption of light

NASA Astrophysics Data System (ADS)

Kettle, Helen; Merchant, Chris J.

2008-08-01

Modeling the vertical penetration of photosynthetically active radiation (PAR) through the ocean, and its utilization by phytoplankton, is fundamental to simulating marine primary production. The variation of attenuation and absorption of light with wavelength suggests that photosynthesis should be modeled at high spectral resolution, but this is computationally expensive. To model primary production in global 3d models, a balance between computer time and accuracy is necessary. We investigate the effects of varying the spectral resolution of the underwater light field and the photosynthetic efficiency of phytoplankton ( α∗), on primary production using a 1d coupled ecosystem ocean turbulence model. The model is applied at three sites in the Atlantic Ocean (CIS (∼60°N), PAP (∼50°N) and ESTOC (∼30°N)) to include the effect of different meteorological forcing and parameter sets. We also investigate three different methods for modeling α∗ - as a fixed constant, varying with both wavelength and chlorophyll concentration [Bricaud, A., Morel, A., Babin, M., Allali, K., Claustre, H., 1998. Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters. Analysis and implications for bio-optical models. J. Geophys. Res. 103, 31033-31044], and using a non-spectral parameterization [Anderson, T.R., 1993. A spectrally averaged model of light penetration and photosynthesis. Limnol. Oceanogr. 38, 1403-1419]. After selecting the appropriate ecosystem parameters for each of the three sites we vary the spectral resolution of light and α∗ from 1 to 61 wavebands and study the results in conjunction with the three different α∗ estimation methods. The results show modeled estimates of ocean primary productivity are highly sensitive to the degree of spectral resolution and α∗. For accurate simulations of primary production and chlorophyll distribution we recommend a spectral resolution of at least six wavebands if α∗ is a function of wavelength and chlorophyll, and three wavebands if α∗ is a fixed value.

Assessing FRET using Spectral Techniques

PubMed Central

Leavesley, Silas J.; Britain, Andrea L.; Cichon, Lauren K.; Nikolaev, Viacheslav O.; Rich, Thomas C.

2015-01-01

Förster resonance energy transfer (FRET) techniques have proven invaluable for probing the complex nature of protein–protein interactions, protein folding, and intracellular signaling events. These techniques have traditionally been implemented with the use of one or more fluorescence band-pass filters, either as fluorescence microscopy filter cubes, or as dichroic mirrors and band-pass filters in flow cytometry. In addition, new approaches for measuring FRET, such as fluorescence lifetime and acceptor photobleaching, have been developed. Hyperspectral techniques for imaging and flow cytometry have also shown to be promising for performing FRET measurements. In this study, we have compared traditional (filter-based) FRET approaches to three spectral-based approaches: the ratio of acceptor-to-donor peak emission, linear spectral unmixing, and linear spectral unmixing with a correction for direct acceptor excitation. All methods are estimates of FRET efficiency, except for one-filter set and three-filter set FRET indices, which are included for consistency with prior literature. In the first part of this study, spectrofluorimetric data were collected from a CFP–Epac–YFP FRET probe that has been used for intracellular cAMP measurements. All comparisons were performed using the same spectrofluorimetric datasets as input data, to provide a relevant comparison. Linear spectral unmixing resulted in measurements with the lowest coefficient of variation (0.10) as well as accurate fits using the Hill equation. FRET efficiency methods produced coefficients of variation of less than 0.20, while FRET indices produced coefficients of variation greater than 8.00. These results demonstrate that spectral FRET measurements provide improved response over standard, filter-based measurements. Using spectral approaches, single-cell measurements were conducted through hyperspectral confocal microscopy, linear unmixing, and cell segmentation with quantitative image analysis. Results from these studies confirmed that spectral imaging is effective for measuring subcellular, time-dependent FRET dynamics and that additional fluorescent signals can be readily separated from FRET signals, enabling multilabel studies of molecular interactions. PMID:23929684

Assessing FRET using spectral techniques.

PubMed

Leavesley, Silas J; Britain, Andrea L; Cichon, Lauren K; Nikolaev, Viacheslav O; Rich, Thomas C

2013-10-01

Förster resonance energy transfer (FRET) techniques have proven invaluable for probing the complex nature of protein-protein interactions, protein folding, and intracellular signaling events. These techniques have traditionally been implemented with the use of one or more fluorescence band-pass filters, either as fluorescence microscopy filter cubes, or as dichroic mirrors and band-pass filters in flow cytometry. In addition, new approaches for measuring FRET, such as fluorescence lifetime and acceptor photobleaching, have been developed. Hyperspectral techniques for imaging and flow cytometry have also shown to be promising for performing FRET measurements. In this study, we have compared traditional (filter-based) FRET approaches to three spectral-based approaches: the ratio of acceptor-to-donor peak emission, linear spectral unmixing, and linear spectral unmixing with a correction for direct acceptor excitation. All methods are estimates of FRET efficiency, except for one-filter set and three-filter set FRET indices, which are included for consistency with prior literature. In the first part of this study, spectrofluorimetric data were collected from a CFP-Epac-YFP FRET probe that has been used for intracellular cAMP measurements. All comparisons were performed using the same spectrofluorimetric datasets as input data, to provide a relevant comparison. Linear spectral unmixing resulted in measurements with the lowest coefficient of variation (0.10) as well as accurate fits using the Hill equation. FRET efficiency methods produced coefficients of variation of less than 0.20, while FRET indices produced coefficients of variation greater than 8.00. These results demonstrate that spectral FRET measurements provide improved response over standard, filter-based measurements. Using spectral approaches, single-cell measurements were conducted through hyperspectral confocal microscopy, linear unmixing, and cell segmentation with quantitative image analysis. Results from these studies confirmed that spectral imaging is effective for measuring subcellular, time-dependent FRET dynamics and that additional fluorescent signals can be readily separated from FRET signals, enabling multilabel studies of molecular interactions. © 2013 International Society for Advancement of Cytometry. Copyright © 2013 International Society for Advancement of Cytometry.

Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels

PubMed Central

2017-01-01

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AICc) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography. PMID:28740757

Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels.

PubMed

Lessios, Nicolas

2017-01-01

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike's information criterion (AIC c ) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis , the branchiopod water flea, Daphnia magna , normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus , which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei . The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography.

Spectral Electroencephalogram Analysis for the Evaluation of Encephalopathy Grade in Children With Acute Liver Failure.

PubMed

Press, Craig A; Morgan, Lindsey; Mills, Michele; Stack, Cynthia V; Goldstein, Joshua L; Alonso, Estella M; Wainwright, Mark S

2017-01-01

Spectral electroencephalogram analysis is a method for automated analysis of electroencephalogram patterns, which can be performed at the bedside. We sought to determine the utility of spectral electroencephalogram for grading hepatic encephalopathy in children with acute liver failure. Retrospective cohort study. Tertiary care pediatric hospital. Patients between 0 and 18 years old who presented with acute liver failure and were admitted to the PICU. None. Electroencephalograms were analyzed by spectral analysis including total power, relative δ, relative θ, relative α, relative β, θ-to-Δ ratio, and α-to-Δ ratio. Normal values and ranges were first derived using normal electroencephalograms from 70 children of 0-18 years old. Age had a significant effect on each variable measured (p < 0.03). Electroencephalograms from 33 patients with acute liver failure were available for spectral analysis. The median age was 4.3 years, 14 of 33 were male, and the majority had an indeterminate etiology of acute liver failure. Neuroimaging was performed in 26 cases and was normal in 20 cases (77%). The majority (64%) survived, and 82% had a good outcome with a score of 1-3 on the Pediatric Glasgow Outcome Scale-Extended at the time of discharge. Hepatic encephalopathy grade correlated with the qualitative visual electroencephalogram scores assigned by blinded neurophysiologists (rs = 0.493; p < 0.006). Spectral electroencephalogram characteristics varied significantly with the qualitative electroencephalogram classification (p < 0.05). Spectral electroencephalogram variables including relative Δ, relative θ, relative α, θ-to-Δ ratio, and α-to-Δ ratio all significantly varied with the qualitative electroencephalogram (p < 0.025). Moderate to severe hepatic encephalopathy was correlated with a total power of less than or equal to 50% of normal for children 0-3 years old, and with a relative θ of less than or equal to 50% normal for children more than 3 years old (p > 0.05). Spectral electroencephalogram classification correlated with outcome (p < 0.05). Spectral electroencephalogram analysis can be used to evaluate even young patients for hepatic encephalopathy and correlates with outcome. Spectral electroencephalogram may allow improved quantitative and reproducible assessment of hepatic encephalopathy grade in children with acute liver failure.

Rapid Prototyping of Hyperspectral Image Analysis Algorithms for Improved Invasive Species Decision Support Tools

NASA Astrophysics Data System (ADS)

Bruce, L. M.; Ball, J. E.; Evangilista, P.; Stohlgren, T. J.

2006-12-01

Nonnative invasive species adversely impact ecosystems, causing loss of native plant diversity, species extinction, and impairment of wildlife habitats. As a result, over the past decade federal and state agencies and nongovernmental organizations have begun to work more closely together to address the management of invasive species. In 2005, approximately 500M dollars was budgeted by U.S. Federal Agencies for the management of invasive species. Despite extensive expenditures, most of the methods used to detect and quantify the distribution of these invaders are ad hoc, at best. Likewise, decisions on the type of management techniques to be used or evaluation of the success of these methods are typically non-systematic. More efficient methods to detect or predict the occurrence of these species, as well as the incorporation of this knowledge into decision support systems, are greatly needed. In this project, rapid prototyping capabilities (RPC) are utilized for an invasive species application. More precisely, our recently developed analysis techniques for hyperspectral imagery are being prototyped for inclusion in the national Invasive Species Forecasting System (ISFS). The current ecological forecasting tools in ISFS will be compared to our hyperspectral-based invasives prediction algorithms to determine if/how the newer algorithms enhance the performance of ISFS. The PIs have researched the use of remotely sensed multispectral and hyperspectral reflectance data for the detection of invasive vegetative species. As a result, the PI has designed, implemented, and benchmarked various target detection systems that utilize remotely sensed data. These systems have been designed to make decisions based on a variety of remotely sensed data, including high spectral/spatial resolution hyperspectral signatures (1000's of spectral bands, such as those measured using ASD handheld devices), moderate spectral/spatial resolution hyperspectral images (100's of spectral bands, such as Hyperion imagery), and low spectral/spatial resolution images (such as MODIS imagery). These algorithms include hyperspectral exploitation methods such as stepwise-LDA band selection, optimized spectral band grouping, and stepwise PCA component selection. The PIs have extensive experience with combining these recently- developed methods with conventional classifiers to form an end-to-end automated target recognition (ATR) system for detecting invasive species. The outputs of these systems can be invasive prediction maps, as well as quantitative accuracy assessments like confusion matrices, user accuracies, and producer accuracies. For all of these research endeavors, the PIs have developed numerous advanced signal and image processing methodologies, as well a suite of associated software modules. However, the use of the prototype software modules has been primarily contained to Mississippi State University. The project described in this presentation and paper will enable future systematic inclusion of these software modules into a DSS with national scope.

Compression of hyper-spectral images using an accelerated nonnegative tensor decomposition

NASA Astrophysics Data System (ADS)

Li, Jin; Liu, Zilong

2017-12-01

Nonnegative tensor Tucker decomposition (NTD) in a transform domain (e.g., 2D-DWT, etc) has been used in the compression of hyper-spectral images because it can remove redundancies between spectrum bands and also exploit spatial correlations of each band. However, the use of a NTD has a very high computational cost. In this paper, we propose a low complexity NTD-based compression method of hyper-spectral images. This method is based on a pair-wise multilevel grouping approach for the NTD to overcome its high computational cost. The proposed method has a low complexity under a slight decrease of the coding performance compared to conventional NTD. We experimentally confirm this method, which indicates that this method has the less processing time and keeps a better coding performance than the case that the NTD is not used. The proposed approach has a potential application in the loss compression of hyper-spectral or multi-spectral images

Spectral difference Lanczos method for efficient time propagation in quantum control theory

NASA Astrophysics Data System (ADS)

Farnum, John D.; Mazziotti, David A.

2004-04-01

Spectral difference methods represent the real-space Hamiltonian of a quantum system as a banded matrix which possesses the accuracy of the discrete variable representation (DVR) and the efficiency of finite differences. When applied to time-dependent quantum mechanics, spectral differences enhance the efficiency of propagation methods for evolving the Schrödinger equation. We develop a spectral difference Lanczos method which is computationally more economical than the sinc-DVR Lanczos method, the split-operator technique, and even the fast-Fourier-Transform Lanczos method. Application of fast propagation is made to quantum control theory where chirped laser pulses are designed to dissociate both diatomic and polyatomic molecules. The specificity of the chirped laser fields is also tested as a possible method for molecular identification and discrimination.

Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging.

PubMed

Sogani, Julie; Morris, Elizabeth A; Kaplan, Jennifer B; D'Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S; Jochelson, Maxine S

2017-01-01

Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material-enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board-approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%-76%) and MR imaging (69%-76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55-0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P < .001 for all). Conclusion There was substantial agreement between readers for BPE detected on CE spectral mammographic and MR images. © RSNA, 2016.

A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

PubMed

Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

2017-07-01

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration.

LOCATING BURIED WORLD WAR 1 MUNITIONS WITH REMOTE SENSING AND GIS

EPA Science Inventory

Remote Sensing is a scientific discipline of non-contact monitoring. It includes a range of technologies that span from aerial photography to advanced spectral imaging and analytical methods. This Session is designed to demonstrate contemporary practical applications of remote ...

Nano-optical scan probes: Opening doors to previously-inaccessible parameter spaces

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

Schuck, James

2014-06-08

I will discuss recent progress on new near-field probe geometries, including the “campanile” geometry, which has been used in recent hyperspectral imaging experiments, providing nanoscale spectral information distinct from what is obtained with other methods. Article not available.

Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm

NASA Astrophysics Data System (ADS)

Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael; Berk, Alexander; Anderson, Gail; Gardner, James; Felde, Gerald

2005-10-01

Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.

Conjugation of antibodies to gold nanorods through Fc portion: synthesis and molecular specific imaging

PubMed Central

Joshi, Pratixa P.; Yoon, Soon Joon; Hardin, William G.; Emelianov, Stanislav; Sokolov, Konstantin V.

2013-01-01

Anisotropic gold nanorods provide a convenient combination of properties, such as tunability of plasmon resonances and strong extinction cross-sections in the near-infrared to red spectral region. These properties have created significant interest in the development of antibody conjugation methods for synthesis of targeted nanorods for a number of biomedical applications, including molecular specific imaging and therapy. Previously published conjugation approaches have achieved molecular specificity. However, the current conjugation methods have several downsides including low stability and potential cytotoxicity of bioconjugates that are produced by electrostatic interactions as well as lack of control over antibody orientation during covalent conjugation. Here we addressed these shortcomings by introducing directional antibody conjugation to the gold nanorod surface. The directional conjugation is achieved through the carbohydrate moiety, which is located on one of the heavy chains of the Fc portion of most antibodies. The carbohydrate is oxidized under mild conditions to a hydrazide reactive aldehyde group. Then, a heterofunctional linker with hydrazide and dithiol groups is used to attach antibodies to gold nanorods. The directional conjugation approach was characterized using electron microscopy, zeta potential and extinction spectra. We also determined spectral changes associated with nanorod aggregation; these spectral changes can be used as a convenient quality control of nanorod bioconjugates. Molecular specificity of the synthesized antibody targeted nanorods was demonstrated using hyperspectral optical and photoacoustic imaging of cancer cell culture models. Additionally, we observed characteristic changes in optical spectra of molecular specific nanorods after their interactions with cancer cells; the observed spectral signatures can be explored for sensitive cancer detection. PMID:23631707

Spectral transformation of ASTER and Landsat TM bands for lithological mapping of Soghan ophiolite complex, south Iran

NASA Astrophysics Data System (ADS)

Pournamdari, Mohsen; Hashim, Mazlan; Pour, Amin Beiranvand

2014-08-01

Spectral transformation methods, including correlation coefficient (CC) and Optimum Index Factor (OIF), band ratio (BR) and principal component analysis (PCA) were applied to ASTER and Landsat TM bands for lithological mapping of Soghan ophiolitic complex in south of Iran. The results indicated that the methods used evidently showed superior outputs for detecting lithological units in ophiolitic complexes. CC and OIF methods were used to establish enhanced Red-Green-Blue (RGB) color combination bands for discriminating lithological units. A specialized band ratio (4/1, 4/5, 4/7 in RGB) was developed using ASTER bands to differentiate lithological units in ophiolitic complexes. The band ratio effectively detected serpentinite dunite as host rock of chromite ore deposits from surrounding lithological units in the study area. Principal component images derived from first three bands of ASTER and Landsat TM produced well results for lithological mapping applications. ASTER bands contain improved spectral characteristics and higher spatial resolution for detecting serpentinite dunite in ophiolitic complexes. The developed approach used in this study offers great potential for lithological mapping using ASTER and Landsat TM bands, which contributes in economic geology for prospecting chromite ore deposits associated with ophiolitic complexes.

Spectral mixture modeling - A new analysis of rock and soil types at the Viking Lander 1 site. [on Mars

NASA Technical Reports Server (NTRS)

Adams, J. B.; Smith, M. O.; Johnson, P. E.

1986-01-01

A Viking Lander 1 image was modeled as mixtures of reflectance spectra of palagonite dust, gray andesitelike rock, and a coarse rocklike soil. The rocks are covered to varying degrees by dust but otherwise appear unweathered. Rocklike soil occurs as lag deposits in deflation zones around stones and on top of a drift and as a layer in a trench dug by the lander. This soil probably is derived from the rocks by wind abrasion and/or spallation. Dust is the major component of the soil and covers most of the surface. The dust is unrelated spectrally to the rock but is equivalent to the global-scale dust observed telescopically. A new method was developed to model a multispectral image as mixtures of end-member spectra and to compare image spectra directly with laboratory reference spectra. The method for the first time uses shade and secondary illumination effects as spectral end-members; thus the effects of topography and illumination on all scales can be isolated or removed. The image was calibrated absolutely from the laboratory spectra, in close agreement with direct calibrations. The method has broad applications to interpreting multispectral images, including satellite images.

Analysis and application of Fourier transform spectroscopy in atmospheric remote sensing

NASA Technical Reports Server (NTRS)

Park, J. H.

1984-01-01

An analysis method for Fourier transform spectroscopy is summarized with applications to various types of distortion in atmospheric absorption spectra. This analysis method includes the fast Fourier transform method for simulating the interferometric spectrum and the nonlinear least-squares method for retrieving the information from a measured spectrum. It is shown that spectral distortions can be simulated quite well and that the correct information can be retrieved from a distorted spectrum by this analysis technique.

Multispectral Wavefronts Retrieval in Digital Holographic Three-Dimensional Imaging Spectrometry

NASA Astrophysics Data System (ADS)

Yoshimori, Kyu

2010-04-01

This paper deals with a recently developed passive interferometric technique for retrieving a set of spectral components of wavefronts that are propagating from a spatially incoherent, polychromatic object. The technique is based on measurement of 5-D spatial coherence function using a suitably designed interferometer. By applying signal processing, including aperture synthesis and spectral decomposition, one may obtains a set of wavefronts of different spectral bands. Since each wavefront is equivalent to the complex Fresnel hologram at a particular spectrum of the polychromatic object, application of the conventional Fresnel transform yields 3-D image of different spectrum. Thus, this technique of multispectral wavefronts retrieval provides a new type of 3-D imaging spectrometry based on a fully passive interferometry. Experimental results are also shown to demonstrate the validity of the method.

Mapping implicit spectral methods to distributed memory architectures

NASA Technical Reports Server (NTRS)

Overman, Andrea L.; Vanrosendale, John

1991-01-01

Spectral methods were proven invaluable in numerical simulation of PDEs (Partial Differential Equations), but the frequent global communication required raises a fundamental barrier to their use on highly parallel architectures. To explore this issue, a 3-D implicit spectral method was implemented on an Intel hypercube. Utilization of about 50 percent was achieved on a 32 node iPSC/860 hypercube, for a 64 x 64 x 64 Fourier-spectral grid; finer grids yield higher utilizations. Chebyshev-spectral grids are more problematic, since plane-relaxation based multigrid is required. However, by using a semicoarsening multigrid algorithm, and by relaxing all multigrid levels concurrently, relatively high utilizations were also achieved in this harder case.

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.

Spatial-spectral preprocessing for endmember extraction on GPU's

NASA Astrophysics Data System (ADS)

Jimenez, Luis I.; Plaza, Javier; Plaza, Antonio; Li, Jun

2016-10-01

Spectral unmixing is focused in the identification of spectrally pure signatures, called endmembers, and their corresponding abundances in each pixel of a hyperspectral image. Mainly focused on the spectral information contained in the hyperspectral images, endmember extraction techniques have recently included spatial information to achieve more accurate results. Several algorithms have been developed for automatic or semi-automatic identification of endmembers using spatial and spectral information, including the spectral-spatial endmember extraction (SSEE) where, within a preprocessing step in the technique, both sources of information are extracted from the hyperspectral image and equally used for this purpose. Previous works have implemented the SSEE technique in four main steps: 1) local eigenvectors calculation in each sub-region in which the original hyperspectral image is divided; 2) computation of the maxima and minima projection of all eigenvectors over the entire hyperspectral image in order to obtain a candidates pixels set; 3) expansion and averaging of the signatures of the candidate set; 4) ranking based on the spectral angle distance (SAD). The result of this method is a list of candidate signatures from which the endmembers can be extracted using various spectral-based techniques, such as orthogonal subspace projection (OSP), vertex component analysis (VCA) or N-FINDR. Considering the large volume of data and the complexity of the calculations, there is a need for efficient implementations. Latest- generation hardware accelerators such as commodity graphics processing units (GPUs) offer a good chance for improving the computational performance in this context. In this paper, we develop two different implementations of the SSEE algorithm using GPUs. Both are based on the eigenvectors computation within each sub-region of the first step, one using the singular value decomposition (SVD) and another one using principal component analysis (PCA). Based on our experiments with hyperspectral data sets, high computational performance is observed in both cases.

Digital staining for histopathology multispectral images by the combined application of spectral enhancement and spectral transformation.

PubMed

Bautista, Pinky A; Yagi, Yukako

2011-01-01

In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.

Ratiometric spectral imaging for fast tumor detection and chemotherapy monitoring in vivo

PubMed Central

Hwang, Jae Youn; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2011-01-01

We report a novel in vivo spectral imaging approach to cancer detection and chemotherapy assessment. We describe and characterize a ratiometric spectral imaging and analysis method and evaluate its performance for tumor detection and delineation by quantitatively monitoring the specific accumulation of targeted gallium corrole (HerGa) into HER2-positive (HER2 +) breast tumors. HerGa temporal accumulation in nude mice bearing HER2 + breast tumors was monitored comparatively by a. this new ratiometric imaging and analysis method; b. established (reflectance and fluorescence) spectral imaging; c. more commonly used fluorescence intensity imaging. We also tested the feasibility of HerGa imaging in vivo using the ratiometric spectral imaging method for tumor detection and delineation. Our results show that the new method not only provides better quantitative information than typical spectral imaging, but also better specificity than standard fluorescence intensity imaging, thus allowing enhanced in vivo outlining of tumors and dynamic, quantitative monitoring of targeted chemotherapy agent accumulation into them. PMID:21721808

Improving reflectance reconstruction from tristimulus values by adaptively combining colorimetric and reflectance similarities

NASA Astrophysics Data System (ADS)

Cao, Bin; Liao, Ningfang; Li, Yasheng; Cheng, Haobo

2017-05-01

The use of spectral reflectance as fundamental color information finds application in diverse fields related to imaging. Many approaches use training sets to train the algorithm used for color classification. In this context, we note that the modification of training sets obviously impacts the accuracy of reflectance reconstruction based on classical reflectance reconstruction methods. Different modifying criteria are not always consistent with each other, since they have different emphases; spectral reflectance similarity focuses on the deviation of reconstructed reflectance, whereas colorimetric similarity emphasizes human perception. We present a method to improve the accuracy of the reconstructed spectral reflectance by adaptively combining colorimetric and spectral reflectance similarities. The different exponential factors of the weighting coefficients were investigated. The spectral reflectance reconstructed by the proposed method exhibits considerable improvements in terms of the root-mean-square error and goodness-of-fit coefficient of the spectral reflectance errors as well as color differences under different illuminants. Our method is applicable to diverse areas such as textiles, printing, art, and other industries.

[An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].

PubMed

Xu, Yonghong; Gao, Shangce; Hao, Xiaofei

2016-04-01

Diffusion tensor imaging(DTI)is a rapid development technology in recent years of magnetic resonance imaging.The diffusion tensor interpolation is a very important procedure in DTI image processing.The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy,but the method does not revise the size of tensors.The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation.Firstly,we decomposed diffusion tensors with the direction of tensors being represented by quaternion.Then we revised the size and direction of the tensor respectively according to different situations.Finally,we acquired the tensor of interpolation point by calculating the weighted average.We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data.The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy(FA)and the determinant of tensors,but also preserve the tensor anisotropy at the same time.In conclusion,the improved method provides a kind of important interpolation method for diffusion tensor image processing.

[Rapid assessment of critical quality attributes of Chinese materia medica (II): strategy of NIR assignment].

PubMed

Pei, Yan-Ling; Wu, Zhi-Sheng; Shi, Xin-Yuan; Zhou, Lu-Wei; Qiao, Yan-Jiang

2014-09-01

The present paper firstly reviewed the research progress and main methods of NIR spectral assignment coupled with our research results. Principal component analysis was focused on characteristic signal extraction to reflect spectral differences. Partial least squares method was concerned with variable selection to discover characteristic absorption band. Two-dimensional correlation spectroscopy was mainly adopted for spectral assignment. Autocorrelation peaks were obtained from spectral changes, which were disturbed by external factors, such as concentration, temperature and pressure. Density functional theory was used to calculate energy from substance structure to establish the relationship between molecular energy and spectra change. Based on the above reviewed method, taking a NIR spectral assignment of chlorogenic acid as example, a reliable spectral assignment for critical quality attributes of Chinese materia medica (CMM) was established using deuterium technology and spectral variable selection. The result demonstrated the assignment consistency according to spectral features of different concentrations of chlorogenic acid and variable selection region of online NIR model in extract process. Although spectral assignment was initial using an active pharmaceutical ingredient, it is meaningful to look forward to the futurity of the complex components in CMM. Therefore, it provided methodology for NIR spectral assignment of critical quality attributes in CMM.

Spectral methods for time dependent problems

NASA Technical Reports Server (NTRS)

Tadmor, Eitan

1990-01-01

Spectral approximations are reviewed for time dependent problems. Some basic ingredients from the spectral Fourier and Chebyshev approximations theory are discussed. A brief survey was made of hyperbolic and parabolic time dependent problems which are dealt with by both the energy method and the related Fourier analysis. The ideas presented above are combined in the study of accuracy stability and convergence of the spectral Fourier approximation to time dependent problems.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

NASA Astrophysics Data System (ADS)

Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66-1.06, 1.06-1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

Scaling dimensions in spectroscopy of soil and vegetation

NASA Astrophysics Data System (ADS)

Malenovský, Zbyněk; Bartholomeus, Harm M.; Acerbi-Junior, Fausto W.; Schopfer, Jürg T.; Painter, Thomas H.; Epema, Gerrit F.; Bregt, Arnold K.

2007-05-01

The paper revises and clarifies definitions of the term scale and scaling conversions for imaging spectroscopy of soil and vegetation. We demonstrate a new four-dimensional scale concept that includes not only spatial but also the spectral, directional and temporal components. Three scaling remote sensing techniques are reviewed: (1) radiative transfer, (2) spectral (un)mixing, and (3) data fusion. Relevant case studies are given in the context of their up- and/or down-scaling abilities over the soil/vegetation surfaces and a multi-source approach is proposed for their integration. Radiative transfer (RT) models are described to show their capacity for spatial, spectral up-scaling, and directional down-scaling within a heterogeneous environment. Spectral information and spectral derivatives, like vegetation indices (e.g. TCARI/OSAVI), can be scaled and even tested by their means. Radiative transfer of an experimental Norway spruce ( Picea abies (L.) Karst.) research plot in the Czech Republic was simulated by the Discrete Anisotropic Radiative Transfer (DART) model to prove relevance of the correct object optical properties scaled up to image data at two different spatial resolutions. Interconnection of the successive modelling levels in vegetation is shown. A future development in measurement and simulation of the leaf directional spectral properties is discussed. We describe linear and/or non-linear spectral mixing techniques and unmixing methods that demonstrate spatial down-scaling. Relevance of proper selection or acquisition of the spectral endmembers using spectral libraries, field measurements, and pure pixels of the hyperspectral image is highlighted. An extensive list of advanced unmixing techniques, a particular example of unmixing a reflective optics system imaging spectrometer (ROSIS) image from Spain, and examples of other mixture applications give insight into the present status of scaling capabilities. Simultaneous spatial and temporal down-scaling by means of a data fusion technique is described. A demonstrative example is given for the moderate resolution imaging spectroradiometer (MODIS) and LANDSAT Thematic Mapper (TM) data from Brazil. Corresponding spectral bands of both sensors were fused via a pyramidal wavelet transform in Fourier space. New spectral and temporal information of the resultant image can be used for thematic classification or qualitative mapping. All three described scaling techniques can be integrated as the relevant methodological steps within a complex multi-source approach. We present this concept of combining numerous optical remote sensing data and methods to generate inputs for ecosystem process models.

WE-FG-207B-02: Material Reconstruction for Spectral Computed Tomography with Detector Response Function

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

Liu, J; Gao, H

2016-06-15

Purpose: Different from the conventional computed tomography (CT), spectral CT based on energy-resolved photon-counting detectors is able to provide the unprecedented material composition. However, an important missing piece for accurate spectral CT is to incorporate the detector response function (DRF), which is distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. Methods: The polyenergetic X-ray forward model takes the DRF into account for accurate material reconstruction. Two image reconstruction methods are proposed: a direct method based on the nonlinear data fidelity from DRF-based forward model; a linear-data-fidelitymore » based method that relies on the spectral rebinning so that the corresponding DRF matrix is invertible. Then the image reconstruction problem is regularized with the isotropic TV term and solved by alternating direction method of multipliers. Results: The simulation results suggest that the proposed methods provided more accurate material compositions than the standard method without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Conclusion: We have proposed material reconstruction methods for spectral CT with DRF, whichprovided more accurate material compositions than the standard methods without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Jiulong Liu and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).« less

Analysis of the spectral vanishing viscosity method for periodic conservation laws

NASA Technical Reports Server (NTRS)

Maday, Yvon; Tadmor, Eitan

1988-01-01

The convergence of the spectral vanishing method for both the spectral and pseudospectral discretizations of the inviscid Burgers' equation is analyzed. It is proven that this kind of vanishing viscosity is responsible for a spectral decay of those Fourier coefficients located toward the end of the computed spectrum; consequently, the discretization error is shown to be spectrally small independent of whether the underlying solution is smooth or not. This in turn implies that the numerical solution remains uniformly bounded and convergence follows by compensated compactness arguments.

Method for enhancing signals transmitted over optical fibers

DOEpatents

Ogle, James W.; Lyons, Peter B.

1983-01-01

A method for spectral equalization of high frequency spectrally broadband signals transmitted through an optical fiber. The broadband signal input is first dispersed by a grating. Narrow spectral components are collected into an array of equalizing fibers. The fibers serve as optical delay lines compensating for material dispersion of each spectral component during transmission. The relative lengths of the individual equalizing fibers are selected to compensate for such prior dispersion. The output of the equalizing fibers couple the spectrally equalized light onto a suitable detector for subsequent electronic processing of the enhanced broadband signal.

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

Development of seismic fragility curves for low-rise masonry infilled reinforced concrete buildings by a coefficient-based method

NASA Astrophysics Data System (ADS)

Su, Ray Kai Leung; Lee, Chien-Liang

2013-06-01

This study presents a seismic fragility analysis and ultimate spectral displacement assessment of regular low-rise masonry infilled (MI) reinforced concrete (RC) buildings using a coefficient-based method. The coefficient-based method does not require a complicated finite element analysis; instead, it is a simplified procedure for assessing the spectral acceleration and displacement of buildings subjected to earthquakes. A regression analysis was first performed to obtain the best-fitting equations for the inter-story drift ratio (IDR) and period shift factor of low-rise MI RC buildings in response to the peak ground acceleration of earthquakes using published results obtained from shaking table tests. Both spectral acceleration- and spectral displacement-based fragility curves under various damage states (in terms of IDR) were then constructed using the coefficient-based method. Finally, the spectral displacements of low-rise MI RC buildings at the ultimate (or nearcollapse) state obtained from this paper and the literature were compared. The simulation results indicate that the fragility curves obtained from this study and other previous work correspond well. Furthermore, most of the spectral displacements of low-rise MI RC buildings at the ultimate state from the literature fall within the bounded spectral displacements predicted by the coefficient-based method.

Research on the shortwave infrared hyperspectral imaging technology based on Integrated Stepwise filter

NASA Astrophysics Data System (ADS)

Wei, Liqing; Xiao, Xizhong; Wang, Yueming; Zhuang, Xiaoqiong; Wang, Jianyu

2017-11-01

Space-borne hyperspectral imagery is an important tool for earth sciences and industrial applications. Higher spatial and spectral resolutions have been sought persistently, although this results in more power, larger volume and weight during a space-borne spectral imager design. For miniaturization of hyperspectral imager and optimization of spectral splitting methods, several methods are compared in this paper. Spectral time delay integration (TDI) method with high transmittance Integrated Stepwise Filter (ISF) is proposed.With the method, an ISF imaging spectrometer with TDI could achieve higher system sensitivity than the traditional prism/grating imaging spectrometer. In addition, the ISF imaging spectrometer performs well in suppressing infrared background radiation produced by instrument. A compact shortwave infrared (SWIR) hyperspectral imager prototype based on HgCdTe covering the spectral range of 2.0-2.5 μm with 6 TDI stages was designed and integrated. To investigate the performance of ISF spectrometer, a method to derive the optimal blocking band curve of the ISF is introduced, along with known error characteristics. To assess spectral performance of the ISF system, a new spectral calibration based on blackbody radiation with temperature scanning is proposed. The results of the imaging experiment showed the merits of ISF. ISF has great application prospects in the field of high sensitivity and high resolution space-borne hyperspectral imagery.

On modelling three-dimensional piezoelectric smart structures with boundary spectral element method

NASA Astrophysics Data System (ADS)

Zou, Fangxin; Aliabadi, M. H.

2017-05-01

The computational efficiency of the boundary element method in elastodynamic analysis can be significantly improved by employing high-order spectral elements for boundary discretisation. In this work, for the first time, the so-called boundary spectral element method is utilised to formulate the piezoelectric smart structures that are widely used in structural health monitoring (SHM) applications. The resultant boundary spectral element formulation has been validated by the finite element method (FEM) and physical experiments. The new formulation has demonstrated a lower demand on computational resources and a higher numerical stability than commercial FEM packages. Comparing to the conventional boundary element formulation, a significant reduction in computational expenses has been achieved. In summary, the boundary spectral element formulation presented in this paper provides a highly efficient and stable mathematical tool for the development of SHM applications.

Contrast-enhanced optical coherence tomography with picomolar sensitivity for functional in vivo imaging

NASA Astrophysics Data System (ADS)

Liba, Orly; Sorelle, Elliott D.; Sen, Debasish; de La Zerda, Adam

2016-03-01

Optical Coherence Tomography (OCT) enables real-time imaging of living tissues at cell-scale resolution over millimeters in three dimensions. Despite these advantages, functional biological studies with OCT have been limited by a lack of exogenous contrast agents that can be distinguished from tissue. Here we report an approach to functional OCT imaging that implements custom algorithms to spectrally identify unique contrast agents: large gold nanorods (LGNRs). LGNRs exhibit 110-fold greater spectral signal per particle than conventional GNRs, which enables detection of individual LGNRs in water and concentrations as low as 250 pM in the circulation of living mice. This translates to ~40 particles per imaging voxel in vivo. Unlike previous implementations of OCT spectral detection, the methods described herein adaptively compensate for depth and processing artifacts on a per sample basis. Collectively, these methods enable high-quality noninvasive contrast-enhanced imaging of OCT in living subjects, including detection of tumor microvasculature at twice the depth achievable with conventional OCT. Additionally, multiplexed detection of spectrally-distinct LGNRs was demonstrated to observe discrete patterns of lymphatic drainage and identify individual lymphangions and lymphatic valve functional states. These capabilities provide a powerful platform for molecular imaging and characterization of tissue noninvasively at cellular resolution, called MOZART.

Ocean wavenumber estimation from wave-resolving time series imagery

USGS Publications Warehouse

Plant, N.G.; Holland, K.T.; Haller, M.C.

2008-01-01

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution). ?? 2008 IEEE.

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.

A fully Bayesian method for jointly fitting instrumental calibration and X-ray spectral models

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

Xu, Jin; Yu, Yaming; Van Dyk, David A.

2014-10-20

Owing to a lack of robust principled methods, systematic instrumental uncertainties have generally been ignored in astrophysical data analysis despite wide recognition of the importance of including them. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. We previously introduced a pragmatic Bayesian method to address this problem. The method is 'pragmatic' in that it introduced an ad hoc technique that simplified computation by neglecting the potential information in the data for narrowing the uncertainty for the calibration product. Following that work, we use amore » principal component analysis to efficiently represent the uncertainty of the effective area of an X-ray (or γ-ray) telescope. Here, however, we leverage this representation to enable a principled, fully Bayesian method that coherently accounts for the calibration uncertainty in high-energy spectral analysis. In this setting, the method is compared with standard analysis techniques and the pragmatic Bayesian method. The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product—here the effective area, conditional on the adopted spectral model. In this way, it can yield more accurate and efficient estimates of the source parameters along with valid estimates of their uncertainty. Provided that the source spectrum can be accurately described by a parameterized model, this method allows rigorous inference about the effective area by quantifying which possible curves are most consistent with the data.« less

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes.

PubMed

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M

2018-04-12

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes

PubMed Central

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M.

2018-01-01

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods. PMID:29649114

Information Extraction from Large-Multi-Layer Social Networks

DTIC Science & Technology

2015-08-06

mization [4]. Methods that fall into this category include spec- tral algorithms, modularity methods, and methods that rely on statistical inference...Snijders and Chris Baerveldt, “A multilevel network study of the effects of delinquent behavior on friendship evolution,” Journal of mathematical sociol- ogy...1970. [10] Ulrike Luxburg, “A tutorial on spectral clustering,” Statistics and Computing, vol. 17, no. 4, pp. 395–416, Dec. 2007. [11] R. A. Fisher, “On

Broadband Studies of Semsmic Sources at Regional and Teleseismic Distances Using Advanced Time Series Analysis Methods. Volume 1.

DTIC Science & Technology

1991-03-21

discussion of spectral factorability and motivations for broadband analysis, the report is subdivided into four main sections. In Section 1.0, we...estimates. The motivation for developing our multi-channel deconvolution method was to gain information about seismic sources, most notably, nuclear...with complex constraints for estimating the rupture history. Such methods (applied mostly to data sets that also include strong rmotion data), were

Time-Spectral Rotorcraft Simulations on Overset Grids

NASA Technical Reports Server (NTRS)

Leffell, Joshua I.; Murman, Scott M.; Pulliam, Thomas H.

2014-01-01

The Time-Spectral method is derived as a Fourier collocation scheme and applied to NASA's overset Reynolds-averaged Navier-Stokes (RANS) solver OVERFLOW. The paper outlines the Time-Spectral OVERFLOWimplementation. Successful low-speed laminar plunging NACA 0012 airfoil simulations demonstrate the capability of the Time-Spectral method to resolve the highly-vortical wakes typical of more expensive three-dimensional rotorcraft configurations. Dealiasing, in the form of spectral vanishing viscosity (SVV), facilitates the convergence of Time-Spectral calculations of high-frequency flows. Finally, simulations of the isolated V-22 Osprey tiltrotor for both hover and forward (edgewise) flight validate the three-dimensional Time-Spectral OVERFLOW implementation. The Time-Spectral hover simulation matches the time-accurate calculation using a single harmonic. Significantly more temporal modes and SVV are required to accurately compute the forward flight case because of its more active, high-frequency wake.

Spectral simplicity of apparent complexity. II. Exact complexities and complexity spectra

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Crutchfield, James P.

2018-03-01

The meromorphic functional calculus developed in Part I overcomes the nondiagonalizability of linear operators that arises often in the temporal evolution of complex systems and is generic to the metadynamics of predicting their behavior. Using the resulting spectral decomposition, we derive closed-form expressions for correlation functions, finite-length Shannon entropy-rate approximates, asymptotic entropy rate, excess entropy, transient information, transient and asymptotic state uncertainties, and synchronization information of stochastic processes generated by finite-state hidden Markov models. This introduces analytical tractability to investigating information processing in discrete-event stochastic processes, symbolic dynamics, and chaotic dynamical systems. Comparisons reveal mathematical similarities between complexity measures originally thought to capture distinct informational and computational properties. We also introduce a new kind of spectral analysis via coronal spectrograms and the frequency-dependent spectra of past-future mutual information. We analyze a number of examples to illustrate the methods, emphasizing processes with multivariate dependencies beyond pairwise correlation. This includes spectral decomposition calculations for one representative example in full detail.

Spectroscopic parallaxes of MAP region stars from UBVRI, DDO, and uvbyH-beta photometry. [Multichannel Astrometric Photometer for astronomical observation

NASA Technical Reports Server (NTRS)

Persinger, Tim; Castelaz, Michael W.

1990-01-01

This paper presents the results of spectral type and luminosity classification of reference stars in the Allegheny Observatory MAP parallax program, using broadband and intermediate-band photometry. In addition to the use of UBVRI and DDO photometric systems, the uvbyH-beta photometric system was included for classification of blue (B - V less than 0.6) reference stars. The stellar classifications made from the photometry are used to determine spectroscopic parallaxes. The spectroscopic parallaxes are used in turn to adjust the relative parallaxes measured with the MAP to absolute parallaxes. A new method for dereddening stars using more than one photometric system is presented. In the process of dereddening, visual extinctions, spectral types, and luminosity classes are determined, as well as a measure of the goodness of fit. The measure of goodness of fit quantifies confidence in the stellar classifications. It is found that the spectral types are reliable to within 2.5 spectral subclasses.

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.

Comparison and evaluation of fusion methods used for GF-2 satellite image in coastal mangrove area

NASA Astrophysics Data System (ADS)

Ling, Chengxing; Ju, Hongbo; Liu, Hua; Zhang, Huaiqing; Sun, Hua

2018-04-01

GF-2 satellite is the highest spatial resolution Remote Sensing Satellite of the development history of China's satellite. In this study, three traditional fusion methods including Brovey, Gram-Schmidt and Color Normalized (CN were used to compare with the other new fusion method NNDiffuse, which used the qualitative assessment and quantitative fusion quality index, including information entropy, variance, mean gradient, deviation index, spectral correlation coefficient. Analysis results show that NNDiffuse method presented the optimum in qualitative and quantitative analysis. It had more effective for the follow up of remote sensing information extraction and forest, wetland resources monitoring applications.

Method for predicting dry mechanical properties from wet wood and standing trees

DOEpatents

Meglen, Robert R.; Kelley, Stephen S.

2003-08-12

A method for determining the dry mechanical strength for a green wood comprising: illuminating a surface of the wood to be determined with light between 350-2,500 nm, the wood having a green moisture content; analyzing the surface using a spectrometric method, the method generating a first spectral data, and using a multivariate analysis to predict the dry mechanical strength of green wood when dry by comparing the first spectral data with a calibration model, the calibration model comprising a second spectrometric method of spectral data obtained from a reference wood having a green moisture content, the second spectral data correlated with a known mechanical strength analytical result obtained from a reference wood when dried and having a dry moisture content.

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

PubMed

Christiansen, Eric M; Yang, Samuel J; Ando, D Michael; Javaherian, Ashkan; Skibinski, Gaia; Lipnick, Scott; Mount, Elliot; O'Neil, Alison; Shah, Kevan; Lee, Alicia K; Goyal, Piyush; Fedus, William; Poplin, Ryan; Esteva, Andre; Berndl, Marc; Rubin, Lee L; Nelson, Philip; Finkbeiner, Steven

2018-04-19

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire. Copyright © 2018 Elsevier Inc. All rights reserved.

Calibration of AIS Data Using Ground-based Spectral Reflectance Measurements

NASA Technical Reports Server (NTRS)

Conel, J. E.

1985-01-01

Present methods of correcting airborne imaging spectrometer (AIS) data for instrumental and atmospheric effects include the flat- or curved-field correction and a deviation-from-the-average adjustment performed on a line-by-line basis throughout the image. Both methods eliminate the atmospheric absorptions, but remove the possibility of studying the atmosphere for its own sake, or of using the atmospheric information present as a possible basis for theoretical modeling. The method discussed here relies on use of ground-based measurements of the surface spectral reflectance in comparison with scanner data to fix in a least-squares sense parameters in a simplified model of the atmosphere on a wavelength-by-wavelength basis. The model parameters (for optically thin conditions) are interpretable in terms of optical depth and scattering phase function, and thus, in principle, provide an approximate description of the atmosphere as a homogeneous body intervening between the sensor and the ground.

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.

[Identification of Dendrobium varieties by Fourier transform infrared spectroscopy combined with spectral retrieval].

PubMed

Liu, Fei; Wang, Yuan-zhong; Deng, Xing-yan; Jin, Hang; Yang, Chun-yan

2014-06-01

The infrared spectral of stems of 165 trees of 23 Dendrobium varieties were obtained by means of Fourier transform infrared spectroscopy technique. The spectra show that the spectra of all the samples were similar, and the main components of stem of Dendrobium is cellulose. By the spectral professional software Omnic8.0, three spectral databases were constructed. Lib01 includes of the average spectral of the first four trees of every variety, while Lib02 and Lib03 are constructed from the first-derivative spectra and the second-derivative spectra of average spectra, separately. The correlation search, the square difference retrieval and the square differential difference retrieval of the spectra are performed with the spectral database Lib01 in the specified range of 1 800-500 cm(-1), and the yield correct rate of 92.7%, 74.5% and 92.7%, respectively. The square differential difference retrieval of the first-derivative spectra and the second-derivative spectra is carried out with Lib02 and Lib03 in the same specified range 1 800-500 cm(-1), and shows correct rate of 93.9% for the former and 90.3% for the later. The results show that the first-derivative spectral retrieval of square differential difference algorithm is more suitabe for discerning Dendrobium varieties, and FTIR combining with the spectral retrieval method can identify different varieties of Dendrobium, and the correlation retrieval, the square differential retrieval, the first-derivative spectra and second-derivative spectra retrieval in the specified spectral range are effective and simple way of distinguishing different varieties of Dendrobium.

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.

Domain decomposition preconditioners for the spectral collocation method

NASA Technical Reports Server (NTRS)

Quarteroni, Alfio; Sacchilandriani, Giovanni

1988-01-01

Several block iteration preconditioners are proposed and analyzed for the solution of elliptic problems by spectral collocation methods in a region partitioned into several rectangles. It is shown that convergence is achieved with a rate which does not depend on the polynomial degree of the spectral solution. The iterative methods here presented can be effectively implemented on multiprocessor systems due to their high degree of parallelism.

Spectral and correlation analysis with applications to middle-atmosphere radars

NASA Technical Reports Server (NTRS)

Rastogi, Prabhat K.

1989-01-01

The correlation and spectral analysis methods for uniformly sampled stationary random signals, estimation of their spectral moments, and problems arising due to nonstationary are reviewed. Some of these methods are already in routine use in atmospheric radar experiments. Other methods based on the maximum entropy principle and time series models have been used in analyzing data, but are just beginning to receive attention in the analysis of radar signals. These methods are also briefly discussed.

Counting spanning trees on fractal graphs and their asymptotic complexity

NASA Astrophysics Data System (ADS)

Anema, Jason A.; Tsougkas, Konstantinos

2016-09-01

Using the method of spectral decimation and a modified version of Kirchhoff's matrix-tree theorem, a closed form solution to the number of spanning trees on approximating graphs to a fully symmetric self-similar structure on a finitely ramified fractal is given in theorem 3.4. We show how spectral decimation implies the existence of the asymptotic complexity constant and obtain some bounds for it. Examples calculated include the Sierpiński gasket, a non-post critically finite analog of the Sierpiński gasket, the Diamond fractal, and the hexagasket. For each example, the asymptotic complexity constant is found.

Development, implementation and evaluation of satellite-aided agricultural monitoring systems

NASA Technical Reports Server (NTRS)

Cicone, R. (Principal Investigator); Crist, E.; Metzler, M.; Parris, T.

1982-01-01

Research supporting the use of remote sensing for inventory and assessment of agricultural commodities is summarized. Three task areas are described: (1) corn and soybean crop spectral/temporal signature characterization; (2) efficient area estimation technology development; and (3) advanced satellite and sensor system definition. Studies include an assessment of alternative green measures from MSS variables; the evaluation of alternative methods for identifying, labeling or classification targets in an automobile procedural context; a comparison of MSS, the advanced very high resolution radiometer and the coastal zone color scanner, as well as a critical assessment of thematic mapper dimensionally and spectral structure.

Quantum walks with an anisotropic coin I: spectral theory

NASA Astrophysics Data System (ADS)

Richard, S.; Suzuki, A.; Tiedra de Aldecoa, R.

2018-02-01

We perform the spectral analysis of the evolution operator U of quantum walks with an anisotropic coin, which include one-defect models, two-phase quantum walks, and topological phase quantum walks as special cases. In particular, we determine the essential spectrum of U, we show the existence of locally U-smooth operators, we prove the discreteness of the eigenvalues of U outside the thresholds, and we prove the absence of singular continuous spectrum for U. Our analysis is based on new commutator methods for unitary operators in a two-Hilbert spaces setting, which are of independent interest.

A statistical evaluation of spectral fingerprinting methods using analysis of variance and principal component analysis

USDA-ARS?s Scientific Manuscript database

Six methods were compared with respect to spectral fingerprinting of a well-characterized series of broccoli samples. Spectral fingerprints were acquired for finely-powdered solid samples using Fourier transform-infrared (IR) and Fourier transform-near infrared (NIR) spectrometry and for aqueous met...

Learning Low-Rank Decomposition for Pan-Sharpening With Spatial-Spectral Offsets.

PubMed

Yang, Shuyuan; Zhang, Kai; Wang, Min

2017-08-25

Finding accurate injection components is the key issue in pan-sharpening methods. In this paper, a low-rank pan-sharpening (LRP) model is developed from a new perspective of offset learning. Two offsets are defined to represent the spatial and spectral differences between low-resolution multispectral and high-resolution multispectral (HRMS) images, respectively. In order to reduce spatial and spectral distortions, spatial equalization and spectral proportion constraints are designed and cast on the offsets, to develop a spatial and spectral constrained stable low-rank decomposition algorithm via augmented Lagrange multiplier. By fine modeling and heuristic learning, our method can simultaneously reduce spatial and spectral distortions in the fused HRMS images. Moreover, our method can efficiently deal with noises and outliers in source images, for exploring low-rank and sparse characteristics of data. Extensive experiments are taken on several image data sets, and the results demonstrate the efficiency of the proposed LRP.

Sensitivity of fenestration solar gain to source spectrum and angle of incidence

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

McCluney, W.R.

1996-12-31

The solar heat gain coefficient (SHGC) is the fraction of solar radiant flux incident on a fenestration system entering a building as heat gain. In general it depends on both the angle of incidence and the spectral distribution of the incident solar radiation. In attempts to improve energy performance and user acceptance of high-performance glazing systems, manufacturers are producing glazing systems with increasing spectral selectivity. This poses potential difficulties for calculations of solar heat gain through windows based upon the use of a single solar spectral weighting function. The sensitivity of modern high-performance glazing systems to both the angle ofmore » incidence and the shape of the incident solar spectrum is examined using a glazing performance simulation program. It is found that as the spectral selectivity of the glazing system increases, the SHGC can vary as the incident spectral distribution varies. The variations can be as great as 50% when using several different representative direct-beam spectra. These include spectra having low and high air masses and a standard spectrum having an air mass of 1.5. The variations can be even greater if clear blue diffuse skylight is considered. It is recommended that the current broad-band shading coefficient method of calculating solar gain be replaced by one that is spectral based.« less

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Site Characterization in the Urban Area of Tijuana, B. C., Mexico by Means of: H/V Spectral Ratios, Spectral Analysis of Surface Waves, and Random Decrement Method

NASA Astrophysics Data System (ADS)

Tapia-Herrera, R.; Huerta-Lopez, C. I.; Martinez-Cruzado, J. A.

2009-05-01

Results of site characterization for an experimental site in the metropolitan area of Tijuana, B. C., Mexico are presented as part of the on-going research in which time series of earthquakes, ambient noise, and induced vibrations were processed with three different methods: H/V spectral ratios, Spectral Analysis of Surface Waves (SASW), and the Random Decrement Method, (RDM). Forward modeling using the wave propagation stiffness matrix method (Roësset and Kausel, 1981) was used to compute the theoretical SH/P, SV/P spectral ratios, and the experimental H/V spectral ratios were computed following the conventional concepts of Fourier analysis. The modeling/comparison between the theoretical and experimental H/V spectral ratios was carried out. For the SASW method the theoretical dispersion curves were also computed and compared with the experimental one, and finally the theoretical free vibration decay curve was compared with the experimental one obtained with the RDM. All three methods were tested with ambient noise, induced vibrations, and earthquake signals. Both experimental spectral ratios obtained with ambient noise as well as earthquake signals agree quite well with the theoretical spectral ratios, particularly at the fundamental vibration frequency of the recording site. Differences between the fundamental vibration frequencies are evident for sites located at alluvial fill (~0.6 Hz) and at sites located at conglomerate/sandstones fill (0.75 Hz). Shear wave velocities for the soft soil layers of the 4-layer discrete soil model ranges as low as 100 m/s and up to 280 m/s. The results with the SASW provided information that allows to identify low velocity layers, not seen before with the traditional seismic methods. The damping estimations obtained with the RDM are within the expected values, and the dominant frequency of the system also obtained with the RDM correlates within the range of plus-minus 20 % with the one obtained by means of the H/V spectral ratio.

Awakening the BALROG: BAyesian Location Reconstruction Of GRBs

NASA Astrophysics Data System (ADS)

Burgess, J. Michael; Yu, Hoi-Fung; Greiner, Jochen; Mortlock, Daniel J.

2018-05-01

The accurate spatial location of gamma-ray bursts (GRBs) is crucial for both accurately characterizing their spectra and follow-up observations by other instruments. The Fermi Gamma-ray Burst Monitor (GBM) has the largest field of view for detecting GRBs as it views the entire unocculted sky, but as a non-imaging instrument it relies on the relative count rates observed in each of its 14 detectors to localize transients. Improving its ability to accurately locate GRBs and other transients is vital to the paradigm of multimessenger astronomy, including the electromagnetic follow-up of gravitational wave signals. Here we present the BAyesian Location Reconstruction Of GRBs (BALROG) method for localizing and characterizing GBM transients. Our approach eliminates the systematics of previous approaches by simultaneously fitting for the location and spectrum of a source. It also correctly incorporates the uncertainties in the location of a transient into the spectral parameters and produces reliable positional uncertainties for both well-localized sources and those for which the GBM data cannot effectively constrain the position. While computationally expensive, BALROG can be implemented to enable quick follow-up of all GBM transient signals. Also, we identify possible response problems that require attention and caution when using standard, public GBM detector response matrices. Finally, we examine the effects of including the uncertainty in location on the spectral parameters of GRB 080916C. We find that spectral parameters change and no extra components are required when these effects are included in contrast to when we use a fixed location. This finding has the potential to alter both the GRB spectral catalogues and the reported spectral composition of some well-known GRBs.

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.

Pre-flight calibration and initial data processing for the ChemCam laser-induced breakdown spectroscopy instrument on the Mars Science Laboratory rover

USGS Publications Warehouse

Wiens, R.C.; Maurice, S.; Lasue, J.; Forni, O.; Anderson, R.B.; Clegg, S.; Bender, S.; Blaney, D.; Barraclough, B.L.; Cousin, A.; DeFlores, L.; Delapp, D.; Dyar, M.D.; Fabre, C.; Gasnault, O.; Lanza, N.; Mazoyer, J.; Melikechi, N.; Meslin, P.-Y.; Newsom, H.; Ollila, A.; Perez, R.; Tokar, R.; Vaniman, D.

2013-01-01

The ChemCam instrument package on the Mars Science Laboratory rover, Curiosity, is the first planetary science instrument to employ laser-induced breakdown spectroscopy (LIBS) to determine the compositions of geological samples on another planet. Pre-processing of the spectra involves subtracting the ambient light background, removing noise, removing the electron continuum, calibrating for the wavelength, correcting for the variable distance to the target, and applying a wavelength-dependent correction for the instrument response. Further processing of the data uses multivariate and univariate comparisons with a LIBS spectral library developed prior to launch as well as comparisons with several on-board standards post-landing. The level-2 data products include semi-quantitative abundances derived from partial least squares regression. A LIBS spectral library was developed using 69 rock standards in the form of pressed powder disks, glasses, and ceramics to minimize heterogeneity on the scale of the observation (350–550 μm dia.). The standards covered typical compositional ranges of igneous materials and also included sulfates, carbonates, and phyllosilicates. The provenance and elemental and mineralogical compositions of these standards are described. Spectral characteristics of this data set are presented, including the size distribution and integrated irradiances of the plasmas, and a proxy for plasma temperature as a function of distance from the instrument. Two laboratory-based clones of ChemCam reside in Los Alamos and Toulouse for the purpose of adding new spectra to the database as the need arises. Sensitivity to differences in wavelength correlation to spectral channels and spectral resolution has been investigated, indicating that spectral registration needs to be within half a pixel and resolution needs to match within 1.5 to 2.6 pixels. Absolute errors are tabulated for derived compositions of each major element in each standard using PLS regression. Sources of errors are investigated and discussed, and methods for improving the analytical accuracy of compositions derived from ChemCam spectra are discussed.

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

NASA Technical Reports Server (NTRS)

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

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

PubMed Central

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

2016-01-01

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

Broadband radio jet emission and variability of γ-ray blazars

NASA Astrophysics Data System (ADS)

Nestoras, Ioannis

2015-07-01

AGN (Active Galactic Nuclei) and in particular their subclass blazars, are among the most energetic objects observed in the universe, featuring extreme phenomenological characteristics such as rapid broadband flux density and polarization variability, fast super--luminal motion, high degree of polarization and a broadband, double-humped spectral energy distribution (SED). The details of the emission processes and violent variability of blazars are still poorly understood. Variability studies give important clues about the size, structure, physics and dynamics of the emitting region making AGN/blazar monitoring programs of uttermost importance in providing the necessary constraints for understanding the origin of energy production. In this framework the F-gamma program was initiated, monitoring monthly 60 fermi detected AGN/blazars at 12 frequencies between 2.6 and 345GHz since 2007. For the thesis in hand observations and data analysis were performed within the realms of the F-gamma program, using the Effelsberg (EB) 100m and Pico Veleta (PV) 30m telescopes at 10 frequency bands ranging from 2.64 to 142GHz. The cm to short-mm variability/spectral characteristics are monitored for a sample of 59 sources for a period of five years enabling for the first time a detailed study of the observed flaring activity in both the light curve and spectral domains for such a large number of sources and such high cadence. Also the observing systems and methods are introduced as well as the data reduction techniques. The thesis at hand is structured as follows: Chapter 3 presents the reduction methods and post measurement corrections applied to the data such as pointing offsets, gain--elevation and sensitivity corrections as well as specific corrections applied for each of the Effelsberg and Pico Veleta observing systems respectively. Chapter 4 presents the analysis tools and methods that were used such as: variability characteristics, flare amplitudes with a new method for estimating the intrinsic standard deviation, flare time scales using Structure Function analysis, spectral indices and spectral peak estimations. Chapter 5 presents the results of the analysis performed upon the five year light curves. The significance of variability through a x^2 test is estimated as well as the flare amplitudes using the intrinsic variability of the light curves along with a new proposed k--index. The introduction of the k--index enables the characterization of the observed variability amplitudes across frequency, thus permitting us to limit the parameter space of various physical models. Also flare time scales, brightness temperatures and Doppler factors are reported. Chapter 6 presents the corresponding analysis in the spectral domain, including results for spectral indices and an S_max - v_max analysis. By determining the spectral peak of every spectra for a selected number of sources, it is possible to track the evolution of the flaring activity in the S_max - v_max plane, enabling us to discriminate between different underlying physical mechanisms that are in action. Finally Chapter 7 includes the overall discussion and a summary of results obtained.

A conservative staggered-grid Chebyshev multidomain method for compressible flows

NASA Technical Reports Server (NTRS)

Kopriva, David A.; Kolias, John H.

1995-01-01

We present a new multidomain spectral collocation method that uses staggered grids for the solution of compressible flow problems. The solution unknowns are defined at the nodes of a Gauss quadrature rule. The fluxes are evaluated at the nodes of a Gauss-Lobatto rule. The method is conservative, free-stream preserving, and exponentially accurate. A significant advantage of the method is that subdomain corners are not included in the approximation, making solutions in complex geometries easier to compute.

The Calibration of AVHRR/3 Visible Dual Gain Using Meteosat-8 as a MODIS Calibration Transfer Medium

NASA Technical Reports Server (NTRS)

Avey, Lance; Garber, Donald; Nguyen, Louis; Minnis, Patrick

2007-01-01

This viewgraph presentation reviews the NOAA-17 AVHRR visible channels calibrated against MET-8/MODIS using dual gain regression methods. The topics include: 1) Motivation; 2) Methodology; 3) Dual Gain Regression Methods; 4) Examples of Regression methods; 5) AVHRR/3 Regression Strategy; 6) Cross-Calibration Method; 7) Spectral Response Functions; 8) MET8/NOAA-17; 9) Example of gain ratio adjustment; 10) Effect of mixed low/high count FOV; 11) Monitor dual gains over time; and 12) Conclusions

Fast sparse Raman spectral unmixing for chemical fingerprinting and quantification

NASA Astrophysics Data System (ADS)

Yaghoobi, Mehrdad; Wu, Di; Clewes, Rhea J.; Davies, Mike E.

2016-10-01

Raman spectroscopy is a well-established spectroscopic method for the detection of condensed phase chemicals. It is based on scattered light from exposure of a target material to a narrowband laser beam. The information generated enables presumptive identification from measuring correlation with library spectra. Whilst this approach is successful in identification of chemical information of samples with one component, it is more difficult to apply to spectral mixtures. The capability of handling spectral mixtures is crucial for defence and security applications as hazardous materials may be present as mixtures due to the presence of degradation, interferents or precursors. A novel method for spectral unmixing is proposed here. Most modern decomposition techniques are based on the sparse decomposition of mixture and the application of extra constraints to preserve the sum of concentrations. These methods have often been proposed for passive spectroscopy, where spectral baseline correction is not required. Most successful methods are computationally expensive, e.g. convex optimisation and Bayesian approaches. We present a novel low complexity sparsity based method to decompose the spectra using a reference library of spectra. It can be implemented on a hand-held spectrometer in near to real-time. The algorithm is based on iteratively subtracting the contribution of selected spectra and updating the contribution of each spectrum. The core algorithm is called fast non-negative orthogonal matching pursuit, which has been proposed by the authors in the context of nonnegative sparse representations. The iteration terminates when the maximum number of expected chemicals has been found or the residual spectrum has a negligible energy, i.e. in the order of the noise level. A backtracking step removes the least contributing spectrum from the list of detected chemicals and reports it as an alternative component. This feature is particularly useful in detection of chemicals with small contributions, which are normally not detected. The proposed algorithm is easily reconfigurable to include new library entries and optional preferential threat searches in the presence of predetermined threat indicators. Under Ministry of Defence funding, we have demonstrated the algorithm for fingerprinting and rough quantification of the concentration of chemical mixtures using a set of reference spectral mixtures. In our experiments, the algorithm successfully managed to detect the chemicals with concentrations below 10 percent. The running time of the algorithm is in the order of one second, using a single core of a desktop computer.

A note on the accuracy of spectral method applied to nonlinear conservation laws

NASA Technical Reports Server (NTRS)

Shu, Chi-Wang; Wong, Peter S.

1994-01-01

Fourier spectral method can achieve exponential accuracy both on the approximation level and for solving partial differential equations if the solutions are analytic. For a linear partial differential equation with a discontinuous solution, Fourier spectral method produces poor point-wise accuracy without post-processing, but still maintains exponential accuracy for all moments against analytic functions. In this note we assess the accuracy of Fourier spectral method applied to nonlinear conservation laws through a numerical case study. We find that the moments with respect to analytic functions are no longer very accurate. However the numerical solution does contain accurate information which can be extracted by a post-processing based on Gegenbauer polynomials.

Mapping bedrock surface contours using the horizontal-to-vertical spectral ratio (HVSR) method near the middle quarter srea, Woodbury, Connecticut

USGS Publications Warehouse

Brown, Craig J.; Voytek, Emily B.; Lane, John W.; Stone, Janet R.

2013-01-01

The bedrock surface contours in Woodbury, Connecticut, were determined downgradient of a commercial zone known as the Middle Quarter area (MQA) using the novel, noninvasive horizontal-to-vertical (H/V) spectral ratio (HVSR) passive seismic geophysical method. Boreholes and monitoring wells had been drilled in this area to characterize the shallow subsurface to within 20 feet (ft) of the land surface, but little was known about the deep subsurface, including sediment thicknesses and depths to bedrock (Starn and Brown, 2007; Brown and others, 2009). Improved information on the altitude of the bedrock surface and its spatial variation was needed for assessment and remediation of chlorinated solvents that have contaminated the overlying glacial aquifer that supplies water to wells in the area.

Semiclassical analysis of spectral singularities and their applications in optics

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

Mostafazadeh, Ali

2011-08-15

Motivated by possible applications of spectral singularities in optics, we develop a semiclassical method of computing spectral singularities. We use this method to examine the spectral singularities of a planar slab gain medium whose gain coefficient varies due to the exponential decay of the intensity of the pumping beam inside the medium. For both singly and doublypumped samples, we obtain universal upper bounds on the decay constant beyond which no lasing occurs. Furthermore, we show that the dependence of the wavelength of the spectral singularities on the value of the decay constant is extremely mild. This is an indication ofmore » the stability of optical spectral singularities.« less

Mapping invasive species and spectral mixture relationships with neotropical woody formations in southeastern Brazil

NASA Astrophysics Data System (ADS)

Amaral, Cibele H.; Roberts, Dar A.; Almeida, Teodoro I. R.; Souza Filho, Carlos R.

2015-10-01

Biological invasion substantially contributes to the increasing extinction rates of native vegetative species. The remote detection and mapping of invasive species is critical for environmental monitoring. This study aims to assess the performance of a Multiple Endmember Spectral Mixture Analysis (MESMA) applied to imaging spectroscopy data for mapping Dendrocalamus sp. (bamboo) and Pinus elliottii L. (slash pine), which are invasive plant species, in a Brazilian neotropical landscape within the tropical Brazilian savanna biome. The work also investigates the spectral mixture between these exotic species and the native woody formations, including woodland savanna, submontane and alluvial seasonal semideciduous forests (SSF). Visible to Shortwave Infrared (VSWIR) imaging spectroscopy data at one-meter spatial resolution were atmospherically corrected and subset into the different spectral ranges (VIS-NIR1: 530-919 nm; and NIR2-SWIR: 1141-2352 nm). The data were further normalized via continuum removal (CR). Multiple endmember selection methods, including Interactive Endmember Selection (IES), Endmember average root mean square error (EAR), Minimum average spectral angle (MASA) and Count-based (CoB) (collectively called EMC), were employed to create endmember libraries for the targeted vegetation classes. The performance of the MESMA was assessed at the pixel and crown scales. Statistically significant differences (α = 0.05) were observed between overall accuracies that were obtained at various spectral ranges. The infrared region (IR) was critical for detecting the vegetation classes using spectral data. The invasive species endmembers exhibited spectral patterns in the IR that were not observed in the native formations. Bamboo was characterized as having a high green vegetation (GV) fraction, lower non-photosynthetic vegetation (NPV) and a low shade fraction, while pine exhibited higher NPV and shade fractions. The invasive species showed a statistically significant larger number of spectra erroneously assigned to the woodland savanna class versus the alluvial and submontane SSF classes. Consequently, the invasive species tended to be overestimated, especially in the woodland savanna. Bamboo was best classified using the VSWIR(CR) data with the EMC endmember selection method (User's accuracy and Producer's accuracy = 98.11% and 72.22%, respectively). Pine was best classified using NIR2-SWIR(CR) data with the IES selected endmembers (97.06% and 62.26%, respectively). The results obtained during the two-endmember modeling were fully translated into the three-endmember unmixed images. The sub-pixel invasive species abundance analysis showed that MESMA performs well when unmixing at the pixel scale and for mapping invasive species fractions in a complex neotropical environment, at pixel and crown scales with 1-m spatial resolution data.

High order spectral volume and spectral difference methods on unstructured grids

NASA Astrophysics Data System (ADS)

Kannan, Ravishekar

The spectral volume (SV) and the spectral difference (SD) methods were developed by Wang and Liu and their collaborators for conservation laws on unstructured grids. They were introduced to achieve high-order accuracy in an efficient manner. Recently, these methods were extended to three-dimensional systems and to the Navier Stokes equations. The simplicity and robustness of these methods have made them competitive against other higher order methods such as the discontinuous Galerkin and residual distribution methods. Although explicit TVD Runge-Kutta schemes for the temporal advancement are easy to implement, they suffer from small time step limited by the Courant-Friedrichs-Lewy (CFL) condition. When the polynomial order is high or when the grid is stretched due to complex geometries or boundary layers, the convergence rate of explicit schemes slows down rapidly. Solution strategies to remedy this problem include implicit methods and multigrid methods. A novel implicit lower-upper symmetric Gauss-Seidel (LU-SGS) relaxation method is employed as an iterative smoother. It is compared to the explicit TVD Runge-Kutta smoothers. For some p-multigrid calculations, combining implicit and explicit smoothers for different p-levels is also studied. The multigrid method considered is nonlinear and uses Full Approximation Scheme (FAS). An overall speed-up factor of up to 150 is obtained using a three-level p-multigrid LU-SGS approach in comparison with the single level explicit method for the Euler equations for the 3rd order SD method. A study of viscous flux formulations was carried out for the SV method. Three formulations were used to discretize the viscous fluxes: local discontinuous Galerkin (LDG), a penalty method and the 2nd method of Bassi and Rebay. Fourier analysis revealed some interesting advantages for the penalty method. These were implemented in the Navier Stokes solver. An implicit and p-multigrid method was also implemented for the above. An overall speed-up factor of up to 1500 is obtained using a three-level p-multigrid LU-SGS approach in comparison with the single level explicit method for the Navier-Stokes equations. The SV method was also extended to turbulent flows. The RANS based SA model was used to close the Reynolds stresses. The numerical results are very promising and indicate that the approaches have great potentials for 3D flow problems.

A novel alignment-free method to classify protein folding types by combining spectral graph clustering with Chou's pseudo amino acid composition.

PubMed

Tripathi, Pooja; Pandey, Paras N

2017-07-07

The present work employs pseudo amino acid composition (PseAAC) for encoding the protein sequences in their numeric form. Later this will be arranged in the similarity matrix, which serves as input for spectral graph clustering method. Spectral methods are used previously also for clustering of protein sequences, but they uses pair wise alignment scores of protein sequences, in similarity matrix. The alignment score depends on the length of sequences, so clustering short and long sequences together may not good idea. Therefore the idea of introducing PseAAC with spectral clustering algorithm came into scene. We extensively tested our method and compared its performance with other existing machine learning methods. It is consistently observed that, the number of clusters that we obtained for a given set of proteins is close to the number of superfamilies in that set and PseAAC combined with spectral graph clustering shows the best classification results. Copyright © 2017 Elsevier Ltd. All rights reserved.

[An improved low spectral distortion PCA fusion method].

PubMed

Peng, Shi; Zhang, Ai-Wu; Li, Han-Lun; Hu, Shao-Xing; Meng, Xian-Gang; Sun, Wei-Dong

2013-10-01

Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.

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

I. W. Ginsberg

Multiresolutional decompositions known as spectral fingerprints are often used to extract spectral features from multispectral/hyperspectral data. In this study, the authors investigate the use of wavelet-based algorithms for generating spectral fingerprints. The wavelet-based algorithms are compared to the currently used method, traditional convolution with first-derivative Gaussian filters. The comparison analyses consists of two parts: (a) the computational expense of the new method is compared with the computational costs of the current method and (b) the outputs of the wavelet-based methods are compared with those of the current method to determine any practical differences in the resulting spectral fingerprints. The resultsmore » show that the wavelet-based algorithms can greatly reduce the computational expense of generating spectral fingerprints, while practically no differences exist in the resulting fingerprints. The analysis is conducted on a database of hyperspectral signatures, namely, Hyperspectral Digital Image Collection Experiment (HYDICE) signatures. The reduction in computational expense is by a factor of about 30, and the average Euclidean distance between resulting fingerprints is on the order of 0.02.« less

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis.

PubMed

Deng, Ning; Li, Zhenye; Pan, Chao; Duan, Huilong

2015-01-01

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

Error analysis for spectral approximation of the Korteweg-De Vries equation

NASA Technical Reports Server (NTRS)

Maday, Y.; recent years.

1987-01-01

The conservation and convergence properties of spectral Fourier methods for the numerical approximation of the Korteweg-de Vries equation are analyzed. It is proved that the (aliased) collocation pseudospectral method enjoys the same convergence properties as the spectral Galerkin method, which is less effective from the computational point of view. This result provides a precise mathematical answer to a question raised by several authors in recent years.

Algorithms for Solvents and Spectral Factors of Matrix Polynomials

DTIC Science & Technology

1981-01-01

spectral factors of matrix polynomials LEANG S. SHIEHt, YIH T. TSAYt and NORMAN P. COLEMANt A generalized Newton method , based on the contracted gradient...of a matrix poly- nomial, is derived for solving the right (left) solvents and spectral factors of matrix polynomials. Two methods of selecting initial...estimates for rapid convergence of the newly developed numerical method are proposed. Also, new algorithms for solving complete sets of the right

Daniell method for power spectral density estimation in atomic force microscopy

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

Labuda, Aleksander

An alternative method for power spectral density (PSD) estimation—the Daniell method—is revisited and compared to the most prevalent method used in the field of atomic force microscopy for quantifying cantilever thermal motion—the Bartlett method. Both methods are shown to underestimate the Q factor of a simple harmonic oscillator (SHO) by a predictable, and therefore correctable, amount in the absence of spurious deterministic noise sources. However, the Bartlett method is much more prone to spectral leakage which can obscure the thermal spectrum in the presence of deterministic noise. By the significant reduction in spectral leakage, the Daniell method leads to amore » more accurate representation of the true PSD and enables clear identification and rejection of deterministic noise peaks. This benefit is especially valuable for the development of automated PSD fitting algorithms for robust and accurate estimation of SHO parameters from a thermal spectrum.« less

Application of the correlation constrained multivariate curve resolution alternating least-squares method for analyte quantitation in the presence of unexpected interferences using first-order instrumental data.

PubMed

Goicoechea, Héctor C; Olivieri, Alejandro C; Tauler, Romà

2010-03-01

Correlation constrained multivariate curve resolution-alternating least-squares is shown to be a feasible method for processing first-order instrumental data and achieve analyte quantitation in the presence of unexpected interferences. Both for simulated and experimental data sets, the proposed method could correctly retrieve the analyte and interference spectral profiles and perform accurate estimations of analyte concentrations in test samples. Since no information concerning the interferences was present in calibration samples, the proposed multivariate calibration approach including the correlation constraint facilitates the achievement of the so-called second-order advantage for the analyte of interest, which is known to be present for more complex higher-order richer instrumental data. The proposed method is tested using a simulated data set and two experimental data systems, one for the determination of ascorbic acid in powder juices using UV-visible absorption spectral data, and another for the determination of tetracycline in serum samples using fluorescence emission spectroscopy.

Mapping of Coral Reef Environment in the Arabian Gulf Using Multispectral Remote Sensing

NASA Astrophysics Data System (ADS)

Ben-Romdhane, H.; Marpu, P. R.; Ghedira, H.; Ouarda, T. B. M. J.

2016-06-01

Coral reefs of the Arabian Gulf are subject to several pressures, thus requiring conservation actions. Well-designed conservation plans involve efficient mapping and monitoring systems. Satellite remote sensing is a cost-effective tool for seafloor mapping at large scales. Multispectral remote sensing of coastal habitats, like those of the Arabian Gulf, presents a special challenge due to their complexity and heterogeneity. The present study evaluates the potential of multispectral sensor DubaiSat-2 in mapping benthic communities of United Arab Emirates. We propose to use a spectral-spatial method that includes multilevel segmentation, nonlinear feature analysis and ensemble learning methods. Support Vector Machine (SVM) is used for comparison of classification performances. Comparative data were derived from the habitat maps published by the Environment Agency-Abu Dhabi. The spectral-spatial method produced 96.41% mapping accuracy. SVM classification is assessed to be 94.17% accurate. The adaptation of these methods can help achieving well-designed coastal management plans in the region.

Spectral distribution of solar radiation

NASA Technical Reports Server (NTRS)

Mecherikunnel, A. T.; Richmond, J.

1980-01-01

Available quantitative data on solar total and spectral irradiance are examined in the context of utilization of solar irradiance for terrestrial applications of solar energy. The extraterrestrial solar total and spectral irradiance values are also reviewed. Computed values of solar spectral irradiance at ground level for different air mass values and various levels of atmospheric pollution or turbidity are presented. Wavelengths are given for computation of solar, absorptance, transmittance and reflectance by the 100 selected-ordinate method and by the 50 selected-ordinate method for air mass 1.5 and 2 solar spectral irradiance for the four levels of atmospheric pollution.

Method for enhancing signals transmitted over optical fibers

DOEpatents

Ogle, J.W.; Lyons, P.B.

1981-02-11

A method for spectral equalization of high frequency spectrally broadband signals transmitted through an optical fiber is disclosed. The broadband signal input is first dispersed by a grating. Narrow spectral components are collected into an array of equalizing fibers. The fibers serve as optical delay lines compensating for material dispersion of each spectral component during transmission. The relative lengths of the individual equalizing fibers are selected to compensate for such prior dispersion. The output of the equalizing fibers couple the spectrally equalized light onto a suitable detector for subsequent electronic processing of the enhanced broadband signal.

Health State Monitoring of Bladed Machinery with Crack Growth Detection in BFG Power Plant Using an Active Frequency Shift Spectral Correction Method.

PubMed

Sun, Weifang; Yao, Bin; He, Yuchao; Chen, Binqiang; Zeng, Nianyin; He, Wangpeng

2017-08-09

Power generation using waste-gas is an effective and green way to reduce the emission of the harmful blast furnace gas (BFG) in pig-iron producing industry. Condition monitoring of mechanical structures in the BFG power plant is of vital importance to guarantee their safety and efficient operations. In this paper, we describe the detection of crack growth of bladed machinery in the BFG power plant via vibration measurement combined with an enhanced spectral correction technique. This technique enables high-precision identification of amplitude, frequency, and phase information (the harmonic information) belonging to deterministic harmonic components within the vibration signals. Rather than deriving all harmonic information using neighboring spectral bins in the fast Fourier transform spectrum, this proposed active frequency shift spectral correction method makes use of some interpolated Fourier spectral bins and has a better noise-resisting capacity. We demonstrate that the identified harmonic information via the proposed method is of suppressed numerical error when the same level of noises is presented in the vibration signal, even in comparison with a Hanning-window-based correction method. With the proposed method, we investigated vibration signals collected from a centrifugal compressor. Spectral information of harmonic tones, related to the fundamental working frequency of the centrifugal compressor, is corrected. The extracted spectral information indicates the ongoing development of an impeller blade crack that occurred in the centrifugal compressor. This method proves to be a promising alternative to identify blade cracks at early stages.

Absolute Radiometric Calibration of Narrow-Swath Imaging Sensors with Reference to Non-Coincident Wide-Swath Sensors

NASA Technical Reports Server (NTRS)

McCorkel, Joel; Thome, Kurtis; Lockwood, Ronald

2012-01-01

An inter-calibration method is developed to provide absolute radiometric calibration of narrow-swath imaging sensors with reference to non-coincident wide-swath sensors. The method predicts at-sensor radiance using non-coincident imagery from the reference sensor and knowledge of spectral reflectance of the test site. The imagery of the reference sensor is restricted to acquisitions that provide similar view and solar illumination geometry to reduce uncertainties due to directional reflectance effects. Spectral reflectance of the test site is found with a simple iterative radiative transfer method using radiance values of a well-understood wide-swath sensor and spectral shape information based on historical ground-based measurements. At-sensor radiance is calculated for the narrow-swath sensor using this spectral reflectance and atmospheric parameters that are also based on historical in situ measurements. Results of the inter-calibration method show agreement on the 2 5 percent level in most spectral regions with the vicarious calibration technique relying on coincident ground-based measurements referred to as the reflectance-based approach. While the variability of the inter-calibration method based on non-coincident image pairs is significantly larger, results are consistent with techniques relying on in situ measurements. The method is also insensitive to spectral differences between the sensors by transferring to surface spectral reflectance prior to prediction of at-sensor radiance. The utility of this inter-calibration method is made clear by its flexibility to utilize image pairings with acquisition dates differing in excess of 30 days allowing frequent absolute calibration comparisons between wide- and narrow-swath sensors.

Method of predicting mechanical properties of decayed wood

DOEpatents

Kelley, Stephen S.

2003-07-15

A method for determining the mechanical properties of decayed wood that has been exposed to wood decay microorganisms, comprising: a) illuminating a surface of decayed wood that has been exposed to wood decay microorganisms with wavelengths from visible and near infrared (VIS-NIR) spectra; b) analyzing the surface of the decayed wood using a spectrometric method, the method generating a first spectral data of wavelengths in VIS-NIR spectra region; and c) using a multivariate analysis to predict mechanical properties of decayed wood by comparing the first spectral data with a calibration model, the calibration model comprising a second spectrometric method of spectral data of wavelengths in VIS-NIR spectra obtained from a reference decay wood, the second spectral data being correlated with a known mechanical property analytical result obtained from the reference decayed wood.

Evaluation of selected spectral vegetation indices in senescent rangeland canopy using Landsat imagery

NASA Astrophysics Data System (ADS)

Striped Face-Collins, Marla

Grassland birds are diminishing more steadily and rapidly than other North American birds in general. The nesting success of some grassland bird species depends on the amount of nonproductive vegetation (NPV). To estimate NPV land managers are currently using the Robel pole visual obstruction reading methods. Researchers with the USDA Agricultural Research Service's (ARS) Northern Great Plains Research Laboratory in Mandan, ND, recently established statistical relationships between photosynthetic vegetation (PV), NPV and spectral vegetation indices (SVIs) derived from more sensitive and more detailed, but less accessible and more costly hyperspectral aerial imagery. This study is an extension of this previous work using spectral vegetation indices collected using the Landsat TM sensor, including simple ratios SWIR-SR (rho2215/rho 1650) and SR71 (rho2215 /rho485) to estimate the amount of NPV and bare ground cover, respectively.

Discontinuous Spectral Difference Method for Conservation Laws on Unstructured Grids

NASA Technical Reports Server (NTRS)

Liu, Yen; Vinokur, Marcel; Wang, Z. J.

2004-01-01

A new, high-order, conservative, and efficient method for conservation laws on unstructured grids is developed. The concept of discontinuous and high-order local representations to achieve conservation and high accuracy is utilized in a manner similar to the Discontinuous Galerkin (DG) and the Spectral Volume (SV) methods, but while these methods are based on the integrated forms of the equations, the new method is based on the differential form to attain a simpler formulation and higher efficiency. A discussion on the Discontinuous Spectral Difference (SD) Method, locations of the unknowns and flux points and numerical results are also presented.

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

NASA Astrophysics Data System (ADS)

Dikmese, Sener; Srinivasan, Sudharsan; Shaat, Musbah; Bader, Faouzi; Renfors, Markku

2014-12-01

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

PubMed

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The Spectral Imaging Toolbox can be downloaded from https://uk.mathworks.com/matlabcentral/fileexchange/62617-spectral-imaging-toolbox .

Compact multispectral photodiode arrays using micropatterned dichroic filters

NASA Astrophysics Data System (ADS)

Chandler, Eric V.; Fish, David E.

2014-05-01

The next generation of multispectral instruments requires significant improvements in both spectral band customization and portability to support the widespread deployment of application-specific optical sensors. The benefits of spectroscopy are well established for numerous applications including biomedical instrumentation, industrial sorting and sensing, chemical detection, and environmental monitoring. In this paper, spectroscopic (and by extension hyperspectral) and multispectral measurements are considered. The technology, tradeoffs, and application fits of each are evaluated. In the majority of applications, monitoring 4-8 targeted spectral bands of optimized wavelength and bandwidth provides the necessary spectral contrast and correlation. An innovative approach integrates precision spectral filters at the photodetector level to enable smaller sensors, simplify optical designs, and reduce device integration costs. This method supports user-defined spectral bands to create application-specific sensors in a small footprint with scalable cost efficiencies. A range of design configurations, filter options and combinations are presented together with typical applications ranging from basic multi-band detection to stringent multi-channel fluorescence measurement. An example implementation packages 8 narrowband silicon photodiodes into a 9x9mm ceramic LCC (leadless chip carrier) footprint. This package is designed for multispectral applications ranging from portable color monitors to purpose- built OEM industrial and scientific instruments. Use of an eight-channel multispectral photodiode array typically eliminates 10-20 components from a device bill-of-materials (BOM), streamlining the optical path and shrinking the footprint by 50% or more. A stepwise design approach for multispectral sensors is discussed - including spectral band definition, optical design tradeoffs and constraints, and device integration from prototype through scalable volume production. Additional customization options are explored for application-specific OEM sensors integrated into portable devices using multispectral photodiode arrays.

Uncertainty of rotating shadowband irradiometers and Si-pyranometers including the spectral irradiance error

NASA Astrophysics Data System (ADS)

Wilbert, Stefan; Kleindiek, Stefan; Nouri, Bijan; Geuder, Norbert; Habte, Aron; Schwandt, Marko; Vignola, Frank

2016-05-01

Concentrating solar power projects require accurate direct normal irradiance (DNI) data including uncertainty specifications for plant layout and cost calculations. Ground measured data are necessary to obtain the required level of accuracy and are often obtained with Rotating Shadowband Irradiometers (RSI) that use photodiode pyranometers and correction functions to account for systematic effects. The uncertainty of Si-pyranometers has been investigated, but so far basically empirical studies were published or decisive uncertainty influences had to be estimated based on experience in analytical studies. One of the most crucial estimated influences is the spectral irradiance error because Si-photodiode-pyranometers only detect visible and color infrared radiation and have a spectral response that varies strongly within this wavelength interval. Furthermore, analytic studies did not discuss the role of correction functions and the uncertainty introduced by imperfect shading. In order to further improve the bankability of RSI and Si-pyranometer data, a detailed uncertainty analysis following the Guide to the Expression of Uncertainty in Measurement (GUM) has been carried out. The study defines a method for the derivation of the spectral error and spectral uncertainties and presents quantitative values of the spectral and overall uncertainties. Data from the PSA station in southern Spain was selected for the analysis. Average standard uncertainties for corrected 10 min data of 2 % for global horizontal irradiance (GHI), and 2.9 % for DNI (for GHI and DNI over 300 W/m²) were found for the 2012 yearly dataset when separate GHI and DHI calibration constants were used. Also the uncertainty in 1 min resolution was analyzed. The effect of correction functions is significant. The uncertainties found in this study are consistent with results of previous empirical studies.

Uncertainty of Rotating Shadowband Irradiometers and Si-Pyranometers Including the Spectral Irradiance Error

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

Wilbert, Stefan; Kleindiek, Stefan; Nouri, Bijan

2016-05-31

Concentrating solar power projects require accurate direct normal irradiance (DNI) data including uncertainty specifications for plant layout and cost calculations. Ground measured data are necessary to obtain the required level of accuracy and are often obtained with Rotating Shadowband Irradiometers (RSI) that use photodiode pyranometers and correction functions to account for systematic effects. The uncertainty of Si-pyranometers has been investigated, but so far basically empirical studies were published or decisive uncertainty influences had to be estimated based on experience in analytical studies. One of the most crucial estimated influences is the spectral irradiance error because Si-photodiode-pyranometers only detect visible andmore » color infrared radiation and have a spectral response that varies strongly within this wavelength interval. Furthermore, analytic studies did not discuss the role of correction functions and the uncertainty introduced by imperfect shading. In order to further improve the bankability of RSI and Si-pyranometer data, a detailed uncertainty analysis following the Guide to the Expression of Uncertainty in Measurement (GUM) has been carried out. The study defines a method for the derivation of the spectral error and spectral uncertainties and presents quantitative values of the spectral and overall uncertainties. Data from the PSA station in southern Spain was selected for the analysis. Average standard uncertainties for corrected 10 min data of 2% for global horizontal irradiance (GHI), and 2.9% for DNI (for GHI and DNI over 300 W/m2) were found for the 2012 yearly dataset when separate GHI and DHI calibration constants were used. Also the uncertainty in 1 min resolution was analyzed. The effect of correction functions is significant. The uncertainties found in this study are consistent with results of previous empirical studies.« less

LANDSAT-4 multispectral scanner (MSS) subsystem radiometric characterization

NASA Technical Reports Server (NTRS)

Alford, W. (Editor); Barker, J. (Editor); Clark, B. P.; Dasgupta, R.

1983-01-01

The multispectral band scanner (mass) and its spectral characteristics are described and methods are given for relating video digital levels on computer compatible tapes to radiance into the sensor. Topics covered include prelaunch calibration procedures and postlaunch radiometric processng. Examples of current data resident on the MSS image processing system are included. The MSS on LANDSAT 4 is compared with the scanners on earlier LANDSAT satellites.

IR spectral properties of dust and ice at the Mars south polar cap

NASA Astrophysics Data System (ADS)

Titus, T. N.; Kieffer, H. H.

2001-11-01

Removal of atmospheric dust effects is required to derive surface IR spectral emissivity. Commonly, the atmospheric-surface separation is based on radiative transfer (RT) spectral inversion methods using nadir-pointing observations. This methodology depends on a priori knowledge of the spectral shape of each atmospheric aerosol (e.g. dust or water ice) and a large thermal contrast between the surface and atmosphere. RT methods fail over the polar caps due to low thermal contrast between the atmosphere and the surface. We have used multi-angle Emission Phase Function (EPF) observations to estimate the opacity spectrum of dust over the springtime south polar cap and the underlying surface radiance, and thus, the surface emissivity. We include a few EPFs from Hellas Basin as a basis for comparisons between the spectral shape of polar and non-polar dust. Surface spectral emissivities over the seasonal cap are compared to CO2 models. Our results show that the spectral shape of the polar dust opacity is not constant, but is a two-parameter family that can be characterized by the 9 um and 20 um opacities. The 9 um opacity varies from 0.15 to 0.45 and characterizes the overall atmospheric conditions. The 9 um to 20 um opacity ratio varies from 2.0 to 5.1, suggesting changes in dust size distribution over the polar caps. Derived surface temperatures from the EPFs confirm that the slightly elevated temperatures (relative to CO2 frost temperature) observed in ``cryptic'' regions are a surface effect, not atmospheric. Comparison of broad-band reflectivity and surface emissivities to model spectra suggest the bright regions (e.g. perennial cap, Mountains of Mitchell) have higher albedos due to a thin surface layer of fine-grain CO2 (perhaps either frost or fractured ice) with an underlying layer of either coarse grain or slab CO2 ice.

Validation of Spectra and Phase in Sub-1 cm-1 Resolution Sum-Frequency Generation Vibrational Spectroscopy through Internal Heterodyne Phase-Resolved Measurement

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

Fu, Li; Chen, Shunli; Wang, Hongfei

2016-03-03

Reliably determination of the spectral features and their phases in sum-frequency generation vibrational spectroscopy (SFG-VS) for surfaces with closely overlapping peaks has been a standing issue. Here we present two approaches towards resolving such issue. The first utilizes the high resolution and accurate lineshape from the recently developed sub-wavenumber high resolution broadband SFG-VS (HR-BB-SFG-VS), from which the detail spectral parameters, including relative spectral phases, of overlapping peaks can be determined through reliable spectral fitting. These results are further validated by using the second method that utilizes the azimuthal angle phase dependence of the z-cut α-quartz crystal, a common phase standard,more » through the spectral interference between the SFG fields of the quartz surface, as the internal phase reference, and the adsorbed molecular layer. Even though this approach is limited to molecular layers that can be transferred or deposited onto the quartz surface, it is simple and straightforward, as it requires only an internal phase standard with a single measurement that is free of phase drifts. More importantly, it provides unambiguous SFG spectral phase information of such surfaces. Using this method, the absolute phase of the molecular susceptibility tensors of the CH3, CH2 and chiral C-H groups in different Langmuir-Blodgett (LB) molecular monolayers and drop-cast peptide films are determined. These two approaches are fully consistent with and complement to each other, making both easily applicable tools in SFG-VS studies. More importantly, as the HR-BB-SFG-VS technique can be easily applied to various surfaces and interfaces, such validation of the spectral and phase information from HR-BB-SFG-VS measurement demonstrates it as one most promising tool for interrogating the detailed structure and interactions of complex molecular interfaces.« less

An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data

USGS Publications Warehouse

Chavez, P.S.

1988-01-01

Digital analysis of remotely sensed data has become an important component of many earth-science studies. These data are often processed through a set of preprocessing or "clean-up" routines that includes a correction for atmospheric scattering, often called haze. Various methods to correct or remove the additive haze component have been developed, including the widely used dark-object subtraction technique. A problem with most of these methods is that the haze values for each spectral band are selected independently. This can create problems because atmospheric scattering is highly wavelength-dependent in the visible part of the electromagnetic spectrum and the scattering values are correlated with each other. Therefore, multispectral data such as from the Landsat Thematic Mapper and Multispectral Scanner must be corrected with haze values that are spectral band dependent. An improved dark-object subtraction technique is demonstrated that allows the user to select a relative atmospheric scattering model to predict the haze values for all the spectral bands from a selected starting band haze value. The improved method normalizes the predicted haze values for the different gain and offset parameters used by the imaging system. Examples of haze value differences between the old and improved methods for Thematic Mapper Bands 1, 2, 3, 4, 5, and 7 are 40.0, 13.0, 12.0, 8.0, 5.0, and 2.0 vs. 40.0, 13.2, 8.9, 4.9, 16.7, and 3.3, respectively, using a relative scattering model of a clear atmosphere. In one Landsat multispectral scanner image the haze value differences for Bands 4, 5, 6, and 7 were 30.0, 50.0, 50.0, and 40.0 for the old method vs. 30.0, 34.4, 43.6, and 6.4 for the new method using a relative scattering model of a hazy atmosphere. ?? 1988.

Extending color primary set in spectral vector error diffusion by multilevel halftoning

NASA Astrophysics Data System (ADS)

Norberg, Ole; Nyström, Daniel

2013-02-01

Ever since its origin in the late 19th century, a color reproduction technology has relied on a trichromatic color reproduction approach. This has been a very successful method and also fundamental for the development of color reproduction devices. Trichromatic color reproduction is sufficient to approximate the range of colors perceived by the human visual system. However, tricromatic systems only have the ability to match colors when the viewing illumination for the reproduction matches that of the original. Furthermore, the advancement of digital printing technology has introduced printing systems with additional color channels. These additional color channels are used to extend the tonal range capabilities in light and dark regions and to increase color gamut. By an alternative approach the addition color channels can also be used to reproduce the spectral information of the original color. A reproduced spectral match will always correspond to original independent of lighting situation. On the other hand, spectral color reproductions also introduce a more complex color processing by spectral color transfer functions and spectral gamut mapping algorithms. In that perspective, spectral vector error diffusion (sVED) look like a tempting approach with a simple workflow where the inverse color transfer function and halftoning is performed simultaneously in one single operation. Essential for the sVED method are the available color primaries, created by mixing process colors. Increased numbers of as well as optimal spectral characteristics of color primaries are expected to significantly improve the color accuracy of the spectral reproduction. In this study, sVED in combination with multilevel halftoning has been applied on a ten channel inkjet system. The print resolution has been reduced and the underlying physical high resolution of the printer has been used to mix additional primaries. With ten ink channels and halfton cells built-up by 2x2 micro dots where each micro dot can be a combination of all ten inks the number of possible ink combinations gets huge. Therefore, the initial study has been focused on including lighter colors to the intrinsic primary set. Results from this study shows that by this approach the color reproduction accuracy increases significantly. The RMS spectral difference to target color for multilevel halftoning is less than 1/6 of the difference achieved by binary halftoning.

DEEP WIDEBAND SINGLE POINTINGS AND MOSAICS IN RADIO INTERFEROMETRY: HOW ACCURATELY DO WE RECONSTRUCT INTENSITIES AND SPECTRAL INDICES OF FAINT SOURCES?

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

Rau, U.; Bhatnagar, S.; Owen, F. N., E-mail: rurvashi@nrao.edu

Many deep wideband wide-field radio interferometric surveys are being designed to accurately measure intensities, spectral indices, and polarization properties of faint source populations. In this paper, we compare various wideband imaging methods to evaluate the accuracy to which intensities and spectral indices of sources close to the confusion limit can be reconstructed. We simulated a wideband single-pointing (C-array, L-Band (1–2 GHz)) and 46-pointing mosaic (D-array, C-Band (4–8 GHz)) JVLA observation using a realistic brightness distribution ranging from 1 μ Jy to 100 mJy and time-, frequency-, polarization-, and direction-dependent instrumental effects. The main results from these comparisons are (a) errors in themore » reconstructed intensities and spectral indices are larger for weaker sources even in the absence of simulated noise, (b) errors are systematically lower for joint reconstruction methods (such as Multi-Term Multi-Frequency-Synthesis (MT-MFS)) along with A-Projection for accurate primary beam correction, and (c) use of MT-MFS for image reconstruction eliminates Clean-bias (which is present otherwise). Auxiliary tests include solutions for deficiencies of data partitioning methods (e.g., the use of masks to remove clean bias and hybrid methods to remove sidelobes from sources left un-deconvolved), the effect of sources not at pixel centers, and the consequences of various other numerical approximations within software implementations. This paper also demonstrates the level of detail at which such simulations must be done in order to reflect reality, enable one to systematically identify specific reasons for every trend that is observed, and to estimate scientifically defensible imaging performance metrics and the associated computational complexity of the algorithms/analysis procedures.« less

Statistics of some atmospheric turbulence records relevant to aircraft response calculations

NASA Technical Reports Server (NTRS)

Mark, W. D.; Fischer, R. W.

1981-01-01

Methods for characterizing atmospheric turbulence are described. The methods illustrated include maximum likelihood estimation of the integral scale and intensity of records obeying the von Karman transverse power spectral form, constrained least-squares estimation of the parameters of a parametric representation of autocorrelation functions, estimation of the power spectra density of the instantaneous variance of a record with temporally fluctuating variance, and estimation of the probability density functions of various turbulence components. Descriptions of the computer programs used in the computations are given, and a full listing of these programs is included.

Common hyperspectral image database design

NASA Astrophysics Data System (ADS)

Tian, Lixun; Liao, Ningfang; Chai, Ali

2009-11-01

This paper is to introduce Common hyperspectral image database with a demand-oriented Database design method (CHIDB), which comprehensively set ground-based spectra, standardized hyperspectral cube, spectral analysis together to meet some applications. The paper presents an integrated approach to retrieving spectral and spatial patterns from remotely sensed imagery using state-of-the-art data mining and advanced database technologies, some data mining ideas and functions were associated into CHIDB to make it more suitable to serve in agriculture, geological and environmental areas. A broad range of data from multiple regions of the electromagnetic spectrum is supported, including ultraviolet, visible, near-infrared, thermal infrared, and fluorescence. CHIDB is based on dotnet framework and designed by MVC architecture including five main functional modules: Data importer/exporter, Image/spectrum Viewer, Data Processor, Parameter Extractor, and On-line Analyzer. The original data were all stored in SQL server2008 for efficient search, query and update, and some advance Spectral image data Processing technology are used such as Parallel processing in C#; Finally an application case is presented in agricultural disease detecting area.

Optimization design of spectral discriminator for high-spectral-resolution lidar based on error analysis.

PubMed

Di, Huige; Zhang, Zhanfei; Hua, Hangbo; Zhang, Jiaqi; Hua, Dengxin; Wang, Yufeng; He, Tingyao

2017-03-06

Accurate aerosol optical properties could be obtained via the high spectral resolution lidar (HSRL) technique, which employs a narrow spectral filter to suppress the Rayleigh or Mie scattering in lidar return signals. The ability of the filter to suppress Rayleigh or Mie scattering is critical for HSRL. Meanwhile, it is impossible to increase the rejection of the filter without limitation. How to optimize the spectral discriminator and select the appropriate suppression rate of the signal is important to us. The HSRL technology was thoroughly studied based on error propagation. Error analyses and sensitivity studies were carried out on the transmittance characteristics of the spectral discriminator. Moreover, ratwo different spectroscopic methods for HSRL were described and compared: one is to suppress the Mie scattering; the other is to suppress the Rayleigh scattering. The corresponding HSRLs were simulated and analyzed. The results show that excessive suppression of Rayleigh scattering or Mie scattering in a high-spectral channel is not necessary if the transmittance of the spectral filter for molecular and aerosol scattering signals can be well characterized. When the ratio of transmittance of the spectral filter for aerosol scattering and molecular scattering is less than 0.1 or greater than 10, the detection error does not change much with its value. This conclusion implies that we have more choices for the high-spectral discriminator in HSRL. Moreover, the detection errors of HSRL regarding the two spectroscopic methods vary greatly with the atmospheric backscattering ratio. To reduce the detection error, it is necessary to choose a reasonable spectroscopic method. The detection method of suppressing the Rayleigh signal and extracting the Mie signal can achieve less error in a clear atmosphere, while the method of suppressing the Mie signal and extracting the Rayleigh signal can achieve less error in a polluted atmosphere.

Integrated ray tracing simulation of annual variation of spectral bio-signatures from cloud free 3D optical Earth model

NASA Astrophysics Data System (ADS)

Ryu, Dongok; Kim, Sug-Whan; Kim, Dae Wook; Lee, Jae-Min; Lee, Hanshin; Park, Won Hyun; Seong, Sehyun; Ham, Sun-Jeong

2010-09-01

Understanding the Earth spectral bio-signatures provides an important reference datum for accurate de-convolution of collapsed spectral signals from potential earth-like planets of other star systems. This study presents a new ray tracing computation method including an improved 3D optical earth model constructed with the coastal line and vegetation distribution data from the Global Ecological Zone (GEZ) map. Using non-Lambertian bidirectional scattering distribution function (BSDF) models, the input earth surface model is characterized with three different scattering properties and their annual variations depending on monthly changes in vegetation distribution, sea ice coverage and illumination angle. The input atmosphere model consists of one layer with Rayleigh scattering model from the sea level to 100 km in altitude and its radiative transfer characteristics is computed for four seasons using the SMART codes. The ocean scattering model is a combination of sun-glint scattering and Lambertian scattering models. The land surface scattering is defined with the semi empirical parametric kernel method used for MODIS and POLDER missions. These three component models were integrated into the final Earth model that was then incorporated into the in-house built integrated ray tracing (IRT) model capable of computing both spectral imaging and radiative transfer performance of a hypothetical space instrument as it observes the Earth from its designated orbit. The IRT model simulation inputs include variation in earth orientation, illuminated phases, and seasonal sea ice and vegetation distribution. The trial simulation runs result in the annual variations in phase dependent disk averaged spectra (DAS) and its associated bio-signatures such as NDVI. The full computational details are presented together with the resulting annual variation in DAS and its associated bio-signatures.

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.

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

NASA Astrophysics Data System (ADS)

Song, Huihui

Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat-MODIS image pairs, we build the corresponding relationship between the difference images of MODIS and ETM+ by training a low- and high-resolution dictionary pair from the given prior image pairs. In the second scenario, i.e., only one Landsat- MODIS image pair being available, we directly correlate MODIS and ETM+ data through an image degradation model. Then, the fusion stage is achieved by super-resolving the MODIS image combining the high-pass modulation in a two-layer fusion framework. Remarkably, the proposed spatial-temporal fusion methods form a unified framework for blending remote sensing images with phenology change or land-cover-type change. Based on the proposed spatial-temporal fusion models, we propose to monitor the land use/land cover changes in Shenzhen, China. As a fast-growing city, Shenzhen faces the problem of detecting the rapid changes for both rational city planning and sustainable development. However, the cloudy and rainy weather in region Shenzhen located makes the capturing circle of high-quality satellite images longer than their normal revisit periods. Spatial-temporal fusion methods are capable to tackle this problem by improving the spatial resolution of images with coarse spatial resolution but frequent temporal coverage, thereby making the detection of rapid changes possible. On two Landsat-MODIS datasets with annual and monthly changes, respectively, we apply the proposed spatial-temporal fusion methods to the task of multiple change detection. Afterward, we propose a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning and sparse non-negative matrix factorization. By combining the spectral information from hyperspectral image, which is characterized by low spatial resolution but high spectral resolution and abbreviated as LSHS, and the spatial information from multispectral image, which is featured by high spatial resolution but low spectral resolution and abbreviated as HSLS, this method aims to generate the fused data with both high spatial and high spectral resolutions. Motivated by the observation that each hyperspectral pixel can be represented by a linear combination of a few endmembers, this method first extracts the spectral bases of LSHS and HSLS images by making full use of the rich spectral information in LSHS data. The spectral bases of these two categories data then formulate a dictionary-pair due to their correspondence in representing each pixel spectra of LSHS data and HSLS data, respectively. Subsequently, the LSHS image is spatially unmixed by representing the HSLS image with respect to the corresponding learned dictionary to derive its representation coefficients. Combining the spectral bases of LSHS data and the representation coefficients of HSLS data, we finally derive the fused data characterized by the spectral resolution of LSHS data and the spatial resolution of HSLS data.

Task-oriented comparison of power spectral density estimation methods for quantifying acoustic attenuation in diagnostic ultrasound using a reference phantom method.

PubMed

Rosado-Mendez, Ivan M; Nam, Kibo; Hall, Timothy J; Zagzebski, James A

2013-07-01

Reported here is a phantom-based comparison of methods for determining the power spectral density (PSD) of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)= α0 f (β), was estimated using a reference phantom method. The power spectral density was estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter-estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error (FE). For parameter estimation regions larger than ~34 pulse lengths (~1 cm for this experiment), an overall power-law FE of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here, the multitaper method reduced the standard deviation of the α0 and β estimates compared with those using the other techniques. The results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound methods.

Preconditioned conjugate residual methods for the solution of spectral equations

NASA Technical Reports Server (NTRS)

Wong, Y. S.; Zang, T. A.; Hussaini, M. Y.

1986-01-01

Conjugate residual methods for the solution of spectral equations are described. An inexact finite-difference operator is introduced as a preconditioner in the iterative procedures. Application of these techniques is limited to problems for which the symmetric part of the coefficient matrix is positive definite. Although the spectral equation is a very ill-conditioned and full matrix problem, the computational effort of the present iterative methods for solving such a system is comparable to that for the sparse matrix equations obtained from the application of either finite-difference or finite-element methods to the same problems. Numerical experiments are shown for a self-adjoint elliptic partial differential equation with Dirichlet boundary conditions, and comparison with other solution procedures for spectral equations is presented.

Finite and spectral cell method for wave propagation in heterogeneous materials

NASA Astrophysics Data System (ADS)

Joulaian, Meysam; Duczek, Sascha; Gabbert, Ulrich; Düster, Alexander

2014-09-01

In the current paper we present a fast, reliable technique for simulating wave propagation in complex structures made of heterogeneous materials. The proposed approach, the spectral cell method, is a combination of the finite cell method and the spectral element method that significantly lowers preprocessing and computational expenditure. The spectral cell method takes advantage of explicit time-integration schemes coupled with a diagonal mass matrix to reduce the time spent on solving the equation system. By employing a fictitious domain approach, this method also helps to eliminate some of the difficulties associated with mesh generation. Besides introducing a proper, specific mass lumping technique, we also study the performance of the low-order and high-order versions of this approach based on several numerical examples. Our results show that the high-order version of the spectral cell method together requires less memory storage and less CPU time than other possible versions, when combined simultaneously with explicit time-integration algorithms. Moreover, as the implementation of the proposed method in available finite element programs is straightforward, these properties turn the method into a viable tool for practical applications such as structural health monitoring [1-3], quantitative ultrasound applications [4], or the active control of vibrations and noise [5, 6].

Analytical design of a hyper-spectral imaging spectrometer utilizing a convex grating

NASA Astrophysics Data System (ADS)

Kim, Seo H.; Kong, Hong J.; Ku, Hana; Lee, Jun H.

2012-09-01

This paper describes about the new design method for hyper-spectral Imaging spectrometers utilizing convex grating. Hyper-spectral imaging systems are power tools in the field of remote sensing. HSI systems collect at least 100 spectral bands of 10~20 nm width. Because the spectral signature is different and induced unique for each material, it should be possible to discriminate between one material and another based on difference in spectral signature of material. I mathematically analyzed parameters for the intellectual initial design. Main concept of this is the derivative of "ring of minimum aberration without vignetting". This work is a kind of analytical design of an Offner imaging spectrometer. Also, several experiment methods will be contrived to evaluate the performance of imaging spectrometer.

Method and system for determining depth distribution of radiation-emitting material located in a source medium and radiation detector system for use therein

DOEpatents

Benke, Roland R.; Kearfott, Kimberlee J.; McGregor, Douglas S.

2004-04-27

A radiation detector system includes detectors having different properties (sensitivity, energy resolution) which are combined so that excellent spectral information may be obtained along with good determinations of the radiation field as a function of position.

Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

NASA Astrophysics Data System (ADS)

Händel, Peter

2006-12-01

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.

Spectral modeling of radiation in combustion systems

NASA Astrophysics Data System (ADS)

Pal, Gopalendu

Radiation calculations are important in combustion due to the high temperatures encountered but has not been studied in sufficient detail in the case of turbulent flames. Radiation calculations for such problems require accurate, robust, and computationally efficient models for the solution of radiative transfer equation (RTE), and spectral properties of radiation. One more layer of complexity is added in predicting the overall heat transfer in turbulent combustion systems due to nonlinear interactions between turbulent fluctuations and radiation. The present work is aimed at the development of finite volume-based high-accuracy thermal radiation modeling, including spectral radiation properties in order to accurately capture turbulence-radiation interactions (TRI) and predict heat transfer in turbulent combustion systems correctly and efficiently. The turbulent fluctuations of temperature and chemical species concentrations have strong effects on spectral radiative intensities, and TRI create a closure problem when the governing partial differential equations are averaged. Recently, several approaches have been proposed to take TRI into account. Among these attempts the most promising approaches are the probability density function (PDF) methods, which can treat nonlinear coupling between turbulence and radiative emission exactly, i.e., "emission TRI". The basic idea of the PDF method is to treat physical variables as random variables and to solve the PDF transport equation stochastically. The actual reacting flow field is represented by a large number of discrete stochastic particles each carrying their own random variable values and evolving with time. The mean value of any function of those random variables, such as the chemical source term, can be evaluated exactly by taking the ensemble average of particles. The local emission term belongs to this class and thus, can be evaluated directly and exactly from particle ensembles. However, the local absorption term involves interactions between the local particle and energy emitted by all other particles and, hence, cannot be obtained from particle ensembles directly. To close the nonlinear coupling between turbulence and absorption, i.e., "absorption TRI", an optically thin fluctuation approximation can be applied to virtually all combustion problems and obtain acceptable accuracy. In the present study a composition-PDF method is applied, in which only the temperature and the species concentrations are treated as random variables. A closely coupled hybrid finite-volume/Monte Carlo scheme is adopted, in which the Monte Carlo method is used to solve the composition-PDF for chemical reactions and the finite volume method is used to solve for the flow field and radiation. Spherical harmonics method-based finite volume solvers (P-1 and P-3) are developed using the data structures of the high fidelity open-source code flow software OpenFOAM. Spectral radiative properties of the participating medium are modeled using full-spectrum k-distribution methods. Advancements of basic k-distribution methods are performed for nongray nonhomogeneous gas- and particulate-phase (soot, fuel droplets, ash, etc.) participating media using multi-scale and multi-group based approaches. These methods achieve close-to benchmark line-by-line (LBL) accuracy in strongly inhomogeneous media at a tiny fraction of LBL's computational cost. A portable spectral module is developed, which includes all the basic to advanced k-distribution methods along with the precompiled accurate and compact k-distribution databases. The P-1 /P-3 RTE solver coupled with the spectral module is used in conjunction with the combined Reynolds-averaged Navier-Stokes (RANS) and composition-PDF-based turbulence-chemistry solver to investigate TRI in multiphase turbulent combustion systems. The combustion solvers developed in this study is employed to simulate several turbulent jet flames, such as Sandia Flame D, and artificial nonsooting and sooting flames derived from Flame D. The effects of combustion chemistry, radiation and TRI on total heat transfer and pollutant (such as NO x) generation are studied for the above flames. The accuracy of the overall combustion solver is assessed by comparing it with the experimental data for Flame D. Comparison of the accuracy and the computational cost among various spectral models and RTE solvers is extensively done on the artificial flames derived from Flame D to demonstrate the necessity of accurate modeling of radiation in combustion problems.

A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

NASA Astrophysics Data System (ADS)

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2010-02-01

Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the AOTF technology and lack of spectral calibration standardization, maintaining long-term stability and compatibility of the acquired hyper-spectral images across different systems is still a challenging problem. Efficiently solving both is essential as the majority of methods for analysis of hyper-spectral images relay on a priori knowledge extracted from large spectral databases, serving as the basis for reliable qualitative or quantitative analysis of various biological samples. In this study, we propose and evaluate fast and reliable spectral calibration of hyper-spectral imaging systems in the short wavelength infrared spectral region. The proposed spectral calibration method is based on light sources or materials, exhibiting distinct spectral features, which enable robust non-rigid registration of the acquired spectra. The calibration accounts for all of the components of a typical hyper-spectral imaging system such as AOTF, light source, lens and optical fibers. The obtained results indicated that practical, fast and reliable spectral calibration of hyper-spectral imaging systems is possible, thereby assuring long-term stability and inter-system compatibility of the acquired hyper-spectral images.

Multispectral image fusion for target detection

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-09-01

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 an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. 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.

Imaging Cellular Dynamics with Spectral Relaxation Imaging Microscopy: Distinct Spectral Dynamics in Golgi Membranes of Living Cells.

PubMed

Lajevardipour, Alireza; Chon, James W M; Chattopadhyay, Amitabha; Clayton, Andrew H A

2016-11-22

Spectral relaxation from fluorescent probes is a useful technique for determining the dynamics of condensed phases. To this end, we have developed a method based on wide-field spectral fluorescence lifetime imaging microscopy to extract spectral relaxation correlation times of fluorescent probes in living cells. We show that measurement of the phase and modulation of fluorescence from two wavelengths permit the identification and determination of excited state lifetimes and spectral relaxation correlation times at a single modulation frequency. For NBD fluorescence in glycerol/water mixtures, the spectral relaxation correlation time determined by our approach exhibited good agreement with published dielectric relaxation measurements. We applied this method to determine the spectral relaxation dynamics in membranes of living cells. Measurements of the Golgi-specific C 6 -NBD-ceramide probe in living HeLa cells revealed sub-nanosecond spectral dynamics in the intracellular Golgi membrane and slower nanosecond spectral dynamics in the extracellular plasma membrane. We interpret the distinct spectral dynamics as a result of structural plasticity of the Golgi membrane relative to more rigid plasma membranes. To the best of our knowledge, these results constitute one of the first measurements of Golgi rotational dynamics.

Spectral colors capture and reproduction based on digital camera

NASA Astrophysics Data System (ADS)

Chen, Defen; Huang, Qingmei; Li, Wei; Lu, Yang

2018-01-01

The purpose of this work is to develop a method for the accurate reproduction of the spectral colors captured by digital camera. The spectral colors being the purest color in any hue, are difficult to reproduce without distortion on digital devices. In this paper, we attempt to achieve accurate hue reproduction of the spectral colors by focusing on two steps of color correction: the capture of the spectral colors and the color characterization of digital camera. Hence it determines the relationship among the spectral color wavelength, the RGB color space of the digital camera device and the CIEXYZ color space. This study also provides a basis for further studies related to the color spectral reproduction on digital devices. In this paper, methods such as wavelength calibration of the spectral colors and digital camera characterization were utilized. The spectrum was obtained through the grating spectroscopy system. A photo of a clear and reliable primary spectrum was taken by adjusting the relative parameters of the digital camera, from which the RGB values of color spectrum was extracted in 1040 equally-divided locations. Calculated using grating equation and measured by the spectrophotometer, two wavelength values were obtained from each location. The polynomial fitting method for the camera characterization was used to achieve color correction. After wavelength calibration, the maximum error between the two sets of wavelengths is 4.38nm. According to the polynomial fitting method, the average color difference of test samples is 3.76. This has satisfied the application needs of the spectral colors in digital devices such as display and transmission.

Spectral Dynamics of Resting State fMRI Within the Ventral Tegmental Area and Dorsal Raphe Nuclei in Medication-Free Major Depressive Disorder in Young Adults.

PubMed

Wohlschläger, Afra; Karne, Harish; Jordan, Denis; Lowe, Mark J; Jones, Stephen E; Anand, Amit

2018-01-01

Background: Dorsal raphe nucleus (DRN) and ventral tegmental area (VTA) are major brainstem monamine nuclei consisting of serotonin and dopamine neurons respectively. Animal studies show that firing patterns in both nuclei are altered when animals exhibit depression like behaviors. Functional MRI studies in humans have shown reduced VTA activation and DRN connectivity in depression. This study for the first time aims at investigating the functional integrity of local neuronal firing concurrently in both the VTA and DRN in vivo in humans using spectral analysis of resting state low frequency fluctuation fMRI. Method: A total of 97 medication-free subjects-67 medication-free young patients (ages 18-30) with major depressive disorder and 30 closely matched healthy controls were included in the study to detect aberrant dynamics in DRN and VTA. For the investigation of altered localized dynamics we conducted power spectral analysis and above this spectral cross correlation between the two groups. Complementary to this, spectral dependence of permutation entropy, an information theoretical measure, was compared between groups. Results: Patients displayed significant spectral slowing in VTA vs. controls ( p = 0.035, corrected). In DRN, spectral slowing was less pronounced, but the amount of slowing significantly correlated with 17-item Hamilton Depression Rating scores of depression severity ( p = 0.038). Signal complexity as assessed via permutation entropy showed spectral alterations inline with the results on spectral slowing. Conclusion: Our results indicate that altered functional dynamics of VTA and DRN in depression can be detected from regional fMRI signal. On this basis, impact of antidepressant treatment and treatment response can be assessed using these markers in future studies.

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.

Petascale turbulence simulation using a highly parallel fast multipole method on GPUs

NASA Astrophysics Data System (ADS)

Yokota, Rio; Barba, L. A.; Narumi, Tetsu; Yasuoka, Kenji

2013-03-01

This paper reports large-scale direct numerical simulations of homogeneous-isotropic fluid turbulence, achieving sustained performance of 1.08 petaflop/s on GPU hardware using single precision. The simulations use a vortex particle method to solve the Navier-Stokes equations, with a highly parallel fast multipole method (FMM) as numerical engine, and match the current record in mesh size for this application, a cube of 40963 computational points solved with a spectral method. The standard numerical approach used in this field is the pseudo-spectral method, relying on the FFT algorithm as the numerical engine. The particle-based simulations presented in this paper quantitatively match the kinetic energy spectrum obtained with a pseudo-spectral method, using a trusted code. In terms of parallel performance, weak scaling results show the FMM-based vortex method achieving 74% parallel efficiency on 4096 processes (one GPU per MPI process, 3 GPUs per node of the TSUBAME-2.0 system). The FFT-based spectral method is able to achieve just 14% parallel efficiency on the same number of MPI processes (using only CPU cores), due to the all-to-all communication pattern of the FFT algorithm. The calculation time for one time step was 108 s for the vortex method and 154 s for the spectral method, under these conditions. Computing with 69 billion particles, this work exceeds by an order of magnitude the largest vortex-method calculations to date.

Convolutional neural networks for vibrational spectroscopic data analysis.

PubMed

Acquarelli, Jacopo; van Laarhoven, Twan; Gerretzen, Jan; Tran, Thanh N; Buydens, Lutgarde M C; Marchiori, Elena

2017-02-15

In this work we show that convolutional neural networks (CNNs) can be efficiently used to classify vibrational spectroscopic data and identify important spectral regions. CNNs are the current state-of-the-art in image classification and speech recognition and can learn interpretable representations of the data. These characteristics make CNNs a good candidate for reducing the need for preprocessing and for highlighting important spectral regions, both of which are crucial steps in the analysis of vibrational spectroscopic data. Chemometric analysis of vibrational spectroscopic data often relies on preprocessing methods involving baseline correction, scatter correction and noise removal, which are applied to the spectra prior to model building. Preprocessing is a critical step because even in simple problems using 'reasonable' preprocessing methods may decrease the performance of the final model. We develop a new CNN based method and provide an accompanying publicly available software. It is based on a simple CNN architecture with a single convolutional layer (a so-called shallow CNN). Our method outperforms standard classification algorithms used in chemometrics (e.g. PLS) in terms of accuracy when applied to non-preprocessed test data (86% average accuracy compared to the 62% achieved by PLS), and it achieves better performance even on preprocessed test data (96% average accuracy compared to the 89% achieved by PLS). For interpretability purposes, our method includes a procedure for finding important spectral regions, thereby facilitating qualitative interpretation of results. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation of spectral distribution of sky radiance using a commercial digital camera.

PubMed

Saito, Masanori; Iwabuchi, Hironobu; Murata, Isao

2016-01-10

Methods for estimating spectral distribution of sky radiance from images captured by a digital camera and for accurately estimating spectral responses of the camera are proposed. Spectral distribution of sky radiance is represented as a polynomial of the wavelength, with coefficients obtained from digital RGB counts by linear transformation. The spectral distribution of radiance as measured is consistent with that obtained by spectrometer and radiative transfer simulation for wavelengths of 430-680 nm, with standard deviation below 1%. Preliminary applications suggest this method is useful for detecting clouds and studying the relation between irradiance at the ground and cloud distribution.

Health State Monitoring of Bladed Machinery with Crack Growth Detection in BFG Power Plant Using an Active Frequency Shift Spectral Correction Method

PubMed Central

Sun, Weifang; Yao, Bin; He, Yuchao; Zeng, Nianyin; He, Wangpeng

2017-01-01

Power generation using waste-gas is an effective and green way to reduce the emission of the harmful blast furnace gas (BFG) in pig-iron producing industry. Condition monitoring of mechanical structures in the BFG power plant is of vital importance to guarantee their safety and efficient operations. In this paper, we describe the detection of crack growth of bladed machinery in the BFG power plant via vibration measurement combined with an enhanced spectral correction technique. This technique enables high-precision identification of amplitude, frequency, and phase information (the harmonic information) belonging to deterministic harmonic components within the vibration signals. Rather than deriving all harmonic information using neighboring spectral bins in the fast Fourier transform spectrum, this proposed active frequency shift spectral correction method makes use of some interpolated Fourier spectral bins and has a better noise-resisting capacity. We demonstrate that the identified harmonic information via the proposed method is of suppressed numerical error when the same level of noises is presented in the vibration signal, even in comparison with a Hanning-window-based correction method. With the proposed method, we investigated vibration signals collected from a centrifugal compressor. Spectral information of harmonic tones, related to the fundamental working frequency of the centrifugal compressor, is corrected. The extracted spectral information indicates the ongoing development of an impeller blade crack that occurred in the centrifugal compressor. This method proves to be a promising alternative to identify blade cracks at early stages. PMID:28792453

[Evaluation of a simplified index (spectral entropy) about sleep state of electrocardiogram recorded by a simplified polygraph, MemCalc-Makin2].

PubMed

Ohisa, Noriko; Ogawa, Hiromasa; Murayama, Nobuki; Yoshida, Katsumi

2010-02-01

Polysomnography (PSG) is the gold standard for the diagnosis of sleep apnea hypopnea syndrome (SAHS), but it takes time to analyze the PSG and PSG cannot be performed repeatedly because of efforts and costs. Therefore, simplified sleep respiratory disorder indices in which are reflected the PSG results are needed. The Memcalc method, which is a combination of the maximum entropy method for spectral analysis and the non-linear least squares method for fitting analysis (Makin2, Suwa Trust, Tokyo, Japan) has recently been developed. Spectral entropy which is derived by the Memcalc method might be useful to expressing the trend of time-series behavior. Spectral entropy of ECG which is calculated with the Memcalc method was evaluated by comparing to the PSG results. Obstructive SAS patients (n = 79) and control volanteer (n = 7) ECG was recorded using MemCalc-Makin2 (GMS) with PSG recording using Alice IV (Respironics) from 20:00 to 6:00. Spectral entropy of ECG, which was calculated every 2 seconds using the Memcalc method, was compared to sleep stages which were analyzed manually from PSG recordings. Spectral entropy value (-0.473 vs. -0.418, p < 0.05) were significantly increased in the OSAHS compared to the control. For the entropy cutoff level of -0.423, sensitivity and specificity for OSAHS were 86.1% and 71.4%, respectively, resulting in a receiver operating characteristic with an area under the curve of 0.837. The absolute value of entropy had inverse correlation with stage 3. Spectral entropy, which was calculated with Memcalc method, might be a possible index evaluating the quality of sleep.

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.

Spectral analysis for GNSS coordinate time series using chirp Fourier transform

NASA Astrophysics Data System (ADS)

Feng, Shengtao; Bo, Wanju; Ma, Qingzun; Wang, Zifan

2017-12-01

Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb-Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.

Software algorithm and hardware design for real-time implementation of new spectral estimator

PubMed Central

2014-01-01

Background Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). Method Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. Results The average interval for a single real-time spectral calculation in software was 3.29 μs for NSE versus 504.5 μs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150× faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. Conclusions The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radiofrequency catheter ablation in real time. PMID:24886214

Spectral Characteristics of Salinized Soils during Microbial Remediation Processes.

PubMed

Ma, Chuang; Shen, Guang-rong; Zhi, Yue-e; Wang, Zi-jun; Zhu, Yun; Li, Xian-hua

2015-09-01

In this study, the spectral reflectance of saline soils, the associated soil salt content (SSC) and the concentrations of salt ions were measured and analysed by tracing the container microbial remediation experiments for saline soil (main salt is sodium chloride) of Dongying City, Shandong Province. The sensitive spectral reflectance bands of saline soils to SSC, Cl- and Na+ in the process of microbial remediation were analysed. The average-dimension reduction of these bands was conducted by using a combination of correlation coefficient and decision coefficient, and by gradually narrowing the sampling interval method. Results showed that the tendency and magnitude of the average spectral reflectance in all bands of saline soils during the total remediation processes were nearly consistent with SSC and with Cl- coocentration, respectively. The degree of salinity of the soil, including SSC and salt ion concentrations, had a significant positive correlation with the spectral reflectance of all bands, particularly in the near-infrared band. The optimal spectral bands of SSC were 1370 to 1445 nm and 1447 to 1608 nm, whereas the optimal spectral bands of Cl- and Na+ were 1336 to 1461 nm and 1471 to 1561 nm, respectively. The relationship model among SSC, soil salt ion concentrations (Cl- and Na+) and soil spectral reflectance of the corresponding optimal spectral band was established. The largest R2 of relationship model between SSC and the average reflectance of associated optimal band reached to 0.95, and RMSEC and RMSEP were 1.076 and 0.591, respectively. Significant statistical analysis of salt factors and soil reflectance for different microbial remediation processes indicated that the spectral response characteristics and sensitivity of SSC to soil reflectance, which implied the feasibility of high spectrum test on soil microbial remediation monitoring, also provided the basis for quick nondestructive monitoring soil bioremediation process by soil spectral reflectance.

Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging

PubMed Central

Morris, Elizabeth A.; Kaplan, Jennifer B.; D’Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S.

2017-01-01

Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material–enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board–approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%–76%) and MR imaging (69%–76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55–0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P < .001 for all). Conclusion There was substantial agreement between readers for BPE detected on CE spectral mammographic and MR images. © RSNA, 2016 PMID:27379544

A Multi-Channel Method for Retrieving Surface Temperature for High-Emissivity Surfaces from Hyperspectral Thermal Infrared Images

PubMed Central

Zhong, Xinke; Labed, Jelila; Zhou, Guoqing; Shao, Kun; Li, Zhao-Liang

2015-01-01

The surface temperature (ST) of high-emissivity surfaces is an important parameter in climate systems. The empirical methods for retrieving ST for high-emissivity surfaces from hyperspectral thermal infrared (HypTIR) images require spectrally continuous channel data. This paper aims to develop a multi-channel method for retrieving ST for high-emissivity surfaces from space-borne HypTIR data. With an assumption of land surface emissivity (LSE) of 1, ST is proposed as a function of 10 brightness temperatures measured at the top of atmosphere by a radiometer having a spectral interval of 800–1200 cm−1 and a spectral sampling frequency of 0.25 cm−1. We have analyzed the sensitivity of the proposed method to spectral sampling frequency and instrumental noise, and evaluated the proposed method using satellite data. The results indicated that the parameters in the developed function are dependent on the spectral sampling frequency and that ST of high-emissivity surfaces can be accurately retrieved by the proposed method if appropriate values are used for each spectral sampling frequency. The results also showed that the accuracy of the retrieved ST is of the order of magnitude of the instrumental noise and that the root mean square error (RMSE) of the ST retrieved from satellite data is 0.43 K in comparison with the AVHRR SST product. PMID:26061199

Compilation of a near-infrared library for the construction of quantitative models of amoxicillin and potassium clavulanate oral dosage forms

NASA Astrophysics Data System (ADS)

Zou, Wen-bo; Chong, Xiao-meng; Wang, Yan; Hu, Chang-qin

2018-05-01

The accuracy of NIR quantitative models depends on calibration samples with concentration variability. Conventional sample collecting methods have some shortcomings especially the time-consuming which remains a bottleneck in the application of NIR models for Process Analytical Technology (PAT) control. A study was performed to solve the problem of sample selection collection for construction of NIR quantitative models. Amoxicillin and potassium clavulanate oral dosage forms were used as examples. The aim was to find a normal approach to rapidly construct NIR quantitative models using an NIR spectral library based on the idea of a universal model [2021]. The NIR spectral library of amoxicillin and potassium clavulanate oral dosage forms was defined and consisted of spectra of 377 batches of samples produced by 26 domestic pharmaceutical companies, including tablets, dispersible tablets, chewable tablets, oral suspensions, and granules. The correlation coefficient (rT) was used to indicate the similarities of the spectra. The samples’ calibration sets were selected from a spectral library according to the median rT of the samples to be analyzed. The rT of the samples selected was close to the median rT. The difference in rT of those samples was 1.0% to 1.5%. We concluded that sample selection is not a problem when constructing NIR quantitative models using a spectral library versus conventional methods of determining universal models. The sample spectra with a suitable concentration range in the NIR models were collected quickly. In addition, the models constructed through this method were more easily targeted.

Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal

NASA Astrophysics Data System (ADS)

Hu, Dewen; Wang, Yucheng; Liu, Yadong; Li, Ming; Liu, Fayi

2010-05-01

An automated method is presented for artery-vein separation in cerebral cortical images recorded with optical imaging of the intrinsic signal. The vessel-type separation method is based on the fact that the spectral distribution of intrinsic physiological oscillations varies from arterial regions to venous regions. In arterial regions, the spectral power is higher in the heartbeat frequency (HF), whereas in venous regions, the spectral power is higher in the respiration frequency (RF). The separation method was begun by extracting the vascular network and its centerline. Then the spectra of the optical intrinsic signals were estimated by the multitaper method. A standard F-test was performed on each discrete frequency point to test the statistical significance at the given level. Four periodic physiological oscillations were examined: HF, RF, and two other eigenfrequencies termed F1 and F2. The separation of arteries and veins was implemented with the fuzzy c-means clustering method and the region-growing approach by utilizing the spectral amplitudes and power-ratio values of the four eigenfrequencies on the vasculature. Subsequently, independent spectral distributions in the arteries, veins, and capillary bed were estimated for comparison, which showed that the spectral distributions of the intrinsic signals were very distinct between the arterial and venous regions.

Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal.

PubMed

Hu, Dewen; Wang, Yucheng; Liu, Yadong; Li, Ming; Liu, Fayi

2010-01-01

An automated method is presented for artery-vein separation in cerebral cortical images recorded with optical imaging of the intrinsic signal. The vessel-type separation method is based on the fact that the spectral distribution of intrinsic physiological oscillations varies from arterial regions to venous regions. In arterial regions, the spectral power is higher in the heartbeat frequency (HF), whereas in venous regions, the spectral power is higher in the respiration frequency (RF). The separation method was begun by extracting the vascular network and its centerline. Then the spectra of the optical intrinsic signals were estimated by the multitaper method. A standard F-test was performed on each discrete frequency point to test the statistical significance at the given level. Four periodic physiological oscillations were examined: HF, RF, and two other eigenfrequencies termed F1 and F2. The separation of arteries and veins was implemented with the fuzzy c-means clustering method and the region-growing approach by utilizing the spectral amplitudes and power-ratio values of the four eigenfrequencies on the vasculature. Subsequently, independent spectral distributions in the arteries, veins, and capillary bed were estimated for comparison, which showed that the spectral distributions of the intrinsic signals were very distinct between the arterial and venous regions.

Improving spectral resolution in spatial encoding dimension of single-scan nuclear magnetic resonance 2D spin echo correlated spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Liangjie; Wei, Zhiliang; Yang, Jian; Lin, Yanqin; Chen, Zhong

2014-11-01

The spatial encoding technique can be used to accelerate the acquisition of multi-dimensional nuclear magnetic resonance spectra. However, with this technique, we have to make trade-offs between the spectral width and the resolution in the spatial encoding dimension (F1 dimension), resulting in the difficulty of covering large spectral widths while preserving acceptable resolutions for spatial encoding spectra. In this study, a selective shifting method is proposed to overcome the aforementioned drawback. This method is capable of narrowing spectral widths and improving spectral resolutions in spatial encoding dimensions by selectively shifting certain peaks in spectra of the ultrafast version of spin echo correlated spectroscopy (UFSECSY). This method can also serve as a powerful tool to obtain high-resolution correlated spectra in inhomogeneous magnetic fields for its resistance to any inhomogeneity in the F1 dimension inherited from UFSECSY. Theoretical derivations and experiments have been carried out to demonstrate performances of the proposed method. Results show that the spectral width in spatial encoding dimension can be reduced by shortening distances between cross peaks and axial peaks with the proposed method and the expected resolution improvement can be achieved. Finally, the shifting-absent spectrum can be recovered readily by post-processing.

Polychromatic spectral pattern analysis of ultra-weak photon emissions from a human body.

PubMed

Kobayashi, Masaki; Iwasa, Torai; Tada, Mika

2016-06-01

Ultra-weak photon emission (UPE), often designated as biophoton emission, is generally observed in a wide range of living organisms, including human beings. This phenomenon is closely associated with reactive oxygen species (ROS) generated during normal metabolic processes and pathological states induced by oxidative stress. Application of UPE extracting the pathophysiological information has long been anticipated because of its potential non-invasiveness, facilitating its diagnostic use. Nevertheless, its weak intensity and UPE mechanism complexity hinder its use for practical applications. Spectroscopy is crucially important for UPE analysis. However, filter-type spectroscopy technique, used as a conventional method for UPE analysis, intrinsically limits its performance because of its monochromatic scheme. To overcome the shortcomings of conventional methods, the authors developed a polychromatic spectroscopy system for UPE spectral pattern analysis. It is based on a highly efficient lens systems and a transmission-type diffraction grating with a highly sensitive, cooled, charge-coupled-device (CCD) camera. Spectral pattern analysis of the human body was done for a fingertip using the developed system. The UPE spectrum covers the spectral range of 450-750nm, with a dominant emission region of 570-670nm. The primary peak is located in the 600-650nm region. Furthermore, application of UPE source exploration was demonstrated with the chemiluminescence spectrum of melanin and coexistence with oxidized linoleic acid. Copyright © 2016 Elsevier B.V. All rights reserved.

Classification of Hyperspectral Data Based on Guided Filtering and Random Forest

NASA Astrophysics Data System (ADS)

Ma, H.; Feng, W.; Cao, X.; Wang, L.

2017-09-01

Hyperspectral images usually consist of more than one hundred spectral bands, which have potentials to provide rich spatial and spectral information. However, the application of hyperspectral data is still challengeable due to "the curse of dimensionality". In this context, many techniques, which aim to make full use of both the spatial and spectral information, are investigated. In order to preserve the geometrical information, meanwhile, with less spectral bands, we propose a novel method, which combines principal components analysis (PCA), guided image filtering and the random forest classifier (RF). In detail, PCA is firstly employed to reduce the dimension of spectral bands. Secondly, the guided image filtering technique is introduced to smooth land object, meanwhile preserving the edge of objects. Finally, the features are fed into RF classifier. To illustrate the effectiveness of the method, we carry out experiments over the popular Indian Pines data set, which is collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. By comparing the proposed method with the method of only using PCA or guided image filter, we find that effect of the proposed method is better.

Tensor-based Dictionary Learning for Spectral CT Reconstruction

PubMed Central

Zhang, Yanbo; Wang, Ge

2016-01-01

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628

Contrast enhancement of subcutaneous blood vessel images by means of visible and near-infrared hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Katrašnik, Jaka; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2009-02-01

Visualization of subcutaneous veins is very difficult with the naked eye, but important for diagnosis of medical conditions and different medical procedures such as catheter insertion and blood withdrawal. Moreover, recent studies showed that the images of subcutaneous veins could be used for biometric identification. The majority of methods used for enhancing the contrast between the subcutaneous veins and surrounding tissue are based on simple imaging systems utilizing CMOS or CCD cameras with LED illumination capable of acquiring images from the near infrared spectral region, usually near 900 nm. However, such simplified imaging methods cannot exploit the full potential of the spectral information. In this paper, a new highly versatile method for enhancing the contrast of subcutaneous veins based on state-of-the-art high-resolution hyper-spectral imaging system utilizing the spectral region from 550 to 1700 nm is presented. First, a detailed analysis of the contrast between the subcutaneous veins and the surrounding tissue as a function of wavelength, for several different positions on the human arm, was performed in order to extract the spectral regions with the highest contrast. The highest contrast images were acquired at 1100 nm, however, combining the individual images from the extracted spectral regions by the proposed contrast enhancement method resulted in a single image with up to ten-fold better contrast. Therefore, the proposed method has proved to be a useful tool for visualization of subcutaneous veins.

Camouflage target detection via hyperspectral imaging plus information divergence measurement

NASA Astrophysics Data System (ADS)

Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

2016-01-01

Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.

Improved Airport Noise Modeling for High Altitudes and Flexible Flight Operations

NASA Technical Reports Server (NTRS)

Forsyth, David W.; Follet, Jesse I.

2006-01-01

The FAA's Integrated Noise Model (INM) is widely used to estimate noise in the vicinity of airports. This study supports the development of standards by which the fleet data in the INM can be updated. A comparison of weather corrections to noise data using INM Spectral Classes is made with the Boeing integrated method. The INM spectral class method is shown to work well, capturing noise level differences due to weather especially at long distances. Two studies conducted at the Denver International Airport are included in the appendices. The two studies adopted different approaches to modeling flight operations at the airport. When compared to the original, year 2000, results, it is apparent that changes made to the INM in terms of modeling processes and databases have resulted in improved agreement between predicted and measured noise levels.

Combining near-field scanning optical microscopy with spectral interferometry for local characterization of the optical electric field in photonic structures.

PubMed

Trägårdh, Johanna; Gersen, Henkjan

2013-07-15

We show how a combination of near-field scanning optical microscopy with crossed beam spectral interferometry allows a local measurement of the spectral phase and amplitude of light propagating in photonic structures. The method only requires measurement at the single point of interest and at a reference point, to correct for the relative phase of the interferometer branches, to retrieve the dispersion properties of the sample. Furthermore, since the measurement is performed in the spectral domain, the spectral phase and amplitude could be retrieved from a single camera frame, here in 70 ms for a signal power of less than 100 pW limited by the dynamic range of the 8-bit camera. The method is substantially faster than most previous time-resolved NSOM methods that are based on time-domain interferometry, which also reduced problems with drift. We demonstrate how the method can be used to measure the refractive index and group velocity in a waveguide structure.

Improving the spectral measurement accuracy based on temperature distribution and spectra-temperature relationship

NASA Astrophysics Data System (ADS)

Li, Zhe; Feng, Jinchao; Liu, Pengyu; Sun, Zhonghua; Li, Gang; Jia, Kebin

2018-05-01

Temperature is usually considered as a fluctuation in near-infrared spectral measurement. Chemometric methods were extensively studied to correct the effect of temperature variations. However, temperature can be considered as a constructive parameter that provides detailed chemical information when systematically changed during the measurement. Our group has researched the relationship between temperature-induced spectral variation (TSVC) and normalized squared temperature. In this study, we focused on the influence of temperature distribution in calibration set. Multi-temperature calibration set selection (MTCS) method was proposed to improve the prediction accuracy by considering the temperature distribution of calibration samples. Furthermore, double-temperature calibration set selection (DTCS) method was proposed based on MTCS method and the relationship between TSVC and normalized squared temperature. We compare the prediction performance of PLS models based on random sampling method and proposed methods. The results from experimental studies showed that the prediction performance was improved by using proposed methods. Therefore, MTCS method and DTCS method will be the alternative methods to improve prediction accuracy in near-infrared spectral measurement.

Analysis of fusion neutron spectral widths in high-foot implosions at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Grim, Gary; Caggiano, Joseph; Callahan, Debra; Casey, Daniel; Cerjan, Charles; Clark, Daniel; Tilo, Doeppner; Eckart, Mark; Field, John; Frenje, Lars; Gatu-Johnson, Maria; Hartouni, Edward; Hatarik, Robert; Hurricane, Omar; Kilkenny, Joseph; Knauer, James; Ma, Tammy; Mannion, Owen; Munro, David; Park, Hye-Sook; Sayre, Daniel; Spears, Brian; Yeamans, Charles

2015-11-01

We present the latest results of thermal temperature analyses of cryogenically layered deuterium-tritium implosions at the NIF using data from the ``High Foot'' campaign. Data from new analysis methods and interpreted in the context of new theoretical developments will be reported. These data will include DD and DT apparent ion temperatures, their uniformity with direction, inferred plasma thermal temperature, as well as the magnitude of non-thermal contributions to the spectral widths. Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.

Spectral line discriminator for passive detection of fluorescence

NASA Technical Reports Server (NTRS)

Kebabian, Paul L. (Inventor)

1996-01-01

A method and apparatus for detecting fluorescence from sunlit plants is based on spectral line discrimination using the A-band and B-band absorption of atmospheric oxygen. Light from a plant including scattered sunlight and the fluorescence from chlorophyll is passed through a chopper into a cell containing low-pressure, high-purity oxygen. A-band or B-band wavelengths present in the light are absorbed by the oxygen in the cell. When the chopper is closed, the absorbed light is remitted as fluorescence into a detector. The intensity of the fluorescence from the oxygen is proportional to the intensity of fluorescence from the plant.

Low Streamflow Forcasting using Minimum Relative Entropy

NASA Astrophysics Data System (ADS)

Cui, H.; Singh, V. P.

2013-12-01

Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.

A spectral tau algorithm based on Jacobi operational matrix for numerical solution of time fractional diffusion-wave equations

NASA Astrophysics Data System (ADS)

Bhrawy, A. H.; Doha, E. H.; Baleanu, D.; Ezz-Eldien, S. S.

2015-07-01

In this paper, an efficient and accurate spectral numerical method is presented for solving second-, fourth-order fractional diffusion-wave equations and fractional wave equations with damping. The proposed method is based on Jacobi tau spectral procedure together with the Jacobi operational matrix for fractional integrals, described in the Riemann-Liouville sense. The main characteristic behind this approach is to reduce such problems to those of solving systems of algebraic equations in the unknown expansion coefficients of the sought-for spectral approximations. The validity and effectiveness of the method are demonstrated by solving five numerical examples. Numerical examples are presented in the form of tables and graphs to make comparisons with the results obtained by other methods and with the exact solutions more easier.

Continuous non-invasive blood glucose monitoring by spectral image differencing method

NASA Astrophysics Data System (ADS)

Huang, Hao; Liao, Ningfang; Cheng, Haobo; Liang, Jing

2018-01-01

Currently, the use of implantable enzyme electrode sensor is the main method for continuous blood glucose monitoring. But the effect of electrochemical reactions and the significant drift caused by bioelectricity in body will reduce the accuracy of the glucose measurements. So the enzyme-based glucose sensors need to be calibrated several times each day by the finger-prick blood corrections. This increases the patient's pain. In this paper, we proposed a method for continuous Non-invasive blood glucose monitoring by spectral image differencing method in the near infrared band. The method uses a high-precision CCD detector to switch the filter in a very short period of time, obtains the spectral images. And then by using the morphological method to obtain the spectral image differences, the dynamic change of blood sugar is reflected in the image difference data. Through the experiment proved that this method can be used to monitor blood glucose dynamically to a certain extent.

A method to establish seismic noise baselines for automated station assessment

USGS Publications Warehouse

McNamara, D.E.; Hutt, C.R.; Gee, L.S.; Benz, H.M.; Buland, R.P.

2009-01-01

We present a method for quantifying station noise baselines and characterizing the spectral shape of out-of-nominal noise sources. Our intent is to automate this method in order to ensure that only the highest-quality data are used in rapid earthquake products at NEIC. In addition, the station noise baselines provide a valuable tool to support the quality control of GSN and ANSS backbone data and metadata. The procedures addressed here are currently in development at the NEIC, and work is underway to understand how quickly changes from nominal can be observed and used within the NEIC processing framework. The spectral methods and software used to compute station baselines and described herein (PQLX) can be useful to both permanent and portable seismic stations operators. Applications include: general seismic station and data quality control (QC), evaluation of instrument responses, assessment of near real-time communication system performance, characterization of site cultural noise conditions, and evaluation of sensor vault design, as well as assessment of gross network capabilities (McNamara et al. 2005). Future PQLX development plans include incorporating station baselines for automated QC methods and automating station status report generation and notification based on user-defined QC parameters. The PQLX software is available through the USGS (http://earthquake. usgs.gov/research/software/pqlx.php) and IRIS (http://www.iris.edu/software/ pqlx/).

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...

Allocation of spectral and spatial modes in multidimensional metro-access optical networks

NASA Astrophysics Data System (ADS)

Gao, Wenbo; Cvijetic, Milorad

2018-04-01

Introduction of spatial division multiplexing (SDM) has added a new dimension in an effort to increase optical fiber channel capacity. At the same time, it can also be explored as an advanced optical networking tool. In this paper, we have investigated the resource allocation to end-users in multidimensional networking structure with plurality of spectral and spatial modes actively deployed in different networking segments. This presents a more comprehensive method as compared to the common practice where the segments of optical network are analyzed independently since the interaction between network hierarchies is included into consideration. We explored the possible transparency from the metro/core network to the optical access network, analyzed the potential bottlenecks from the network architecture perspective, and identified an optimized network structure. In our considerations, the viability of optical grooming through the entire hierarchical all-optical network is investigated by evaluating the effective utilization and spectral efficiency of the network architecture.

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

Improving 3D Wavelet-Based Compression of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Klimesh, Matthew; Kiely, Aaron; Xie, Hua; Aranki, Nazeeh

2009-01-01

Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a manner similar to that of a baseline hyperspectral- image-compression method. The mean values are encoded in the compressed bit stream and added back to the data at the appropriate decompression step. The overhead incurred by encoding the mean values only a few bits per spectral band is negligible with respect to the huge size of a typical hyperspectral data set. The other method is denoted modified decomposition. This method is so named because it involves a modified version of a commonly used multiresolution wavelet decomposition, known in the art as the 3D Mallat decomposition, in which (a) the first of multiple stages of a 3D wavelet transform is applied to the entire dataset and (b) subsequent stages are applied only to the horizontally-, vertically-, and spectrally-low-pass subband from the preceding stage. In the modified decomposition, in stages after the first, not only is the spatially-low-pass, spectrally-low-pass subband further decomposed, but also spatially-low-pass, spectrally-high-pass subbands are further decomposed spatially. Either method can be used alone to improve the quality of a reconstructed image (see figure). Alternatively, the two methods can be combined by first performing modified decomposition, then subtracting the mean values from spatial planes of spatially-low-pass subbands.

Calculation of day and night emittance values

NASA Technical Reports Server (NTRS)

Kahle, Anne B.

1986-01-01

In July 1983, the Thermal Infrared Multispectral Scanner (TIMS) was flown over Death Valley, California on both a midday and predawn flight within a two-day period. The availability of calibrated digital data permitted the calculation of day and night surface temperature and surface spectral emittance. Image processing of the data included panorama correction and calibration to radiance using the on-board black bodies and the measured spectral response of each channel. Scene-dependent isolated-point noise due to bit drops, was located by its relatively discontinuous values and replaced by the average of the surrounding data values. A method was developed in order to separate the spectral and temperature information contained in the TIMS data. Night and day data sets were processed. The TIMS is unique in allowing collection of both spectral emittance and thermal information in digital format with the same airborne scanner. For the first time it was possible to produce day and night emittance images of the same area, coregistered. These data add to an understanding of the physical basis for the discrimination of difference in surface materials afforded by TIMS.

Diurnal changes in the power spectral characteristics of eye movements and heart rate variability in the human fetus at term.

PubMed

Morokuma, S; Horimoto, N; Nakano, H

2001-08-01

It is well known that 1/f characteristics in power spectral patterns exist in various biological factors including heart rate variability. In the present study, we tried to elucidate the diurnal variation in spectral properties of eye movement and heart rate variability in the human fetus at term, via continuous 24-h observation of both these parameters. Studied were five uncomplicated fetuses at term. We observed eye movement and fetal heart rate (FHR) with real-time ultrasound and Doppler cardiotocograph, respectively, and analyzed the diurnal change in spectral properties, using the maximum entropy method. In four of five cases, the slope values of power spectra for both eye movement frequency and FHR, ranging approximately between 0.5 and 1.8, indicated diurnal variation, where the slopes tended to have high values during the day and low values at night. These findings suggest that, in the human fetus at term, eye movement and FHR are under the control of a common central mechanism, and this center changes its complexity as seen through diurnal rhythm.

Sound Transmission through Cylindrical Shell Structures Excited by Boundary Layer Pressure Fluctuations

NASA Technical Reports Server (NTRS)

Tang, Yvette Y.; Silcox, Richard J.; Robinson, Jay H.

1996-01-01

This paper examines sound transmission into two concentric cylindrical sandwich shells subject to turbulent flow on the exterior surface of the outer shell. The interior of the shells is filled with fluid medium and there is an airgap between the shells in the annular space. The description of the pressure field is based on the cross-spectral density formulation of Corcos, Maestrello, and Efimtsov models of the turbulent boundary layer. The classical thin shell theory and the first-order shear deformation theory are applied for the inner and outer shells, respectively. Modal expansion and the Galerkin approach are used to obtain closed-form solutions for the shell displacements and the radiation and transmission pressures in the cavities including both the annular space and the interior. The average spectral density of the structural responses and the transmitted interior pressures are expressed explicitly in terms of the summation of the cross-spectral density of generalized force induced by the boundary layer turbulence. The effects of acoustic and hydrodynamic coincidences on the spectral density are observed. Numerical examples are presented to illustrate the method for both subsonic and supersonic flows.

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

Zhang, Libing; Lu, Zhou; Velarde Ruiz Esparza, Luis A.

Here we reported the first sub-wavenumber high-resolution broadband sum frequency generation vibrational spectroscopy (HR-BB-SFG-VS) study on both the C-H and O-H region spectra of crystalline cellulose. HR-BB-SFG-VS has about 10 times better resolution than the conventional scanning SFG-VS and is known to be able to measure the intrinsic spectral lineshape and to resolve much more spectral details. With HR-BB-SFG-VS, we found that in cellulose from different sources, including Avicel and cellulose crystals isolated from algae Valonia (Iα) and tunicates (Iβ), the spectral signatures in the OH regions were unique for different allomorphs, i.e. Iα and Iβ, while the spectral signaturesmore » in the C-H regions varied in all samples examined. Even though the origin of the different behaviors of the crystalline cellulose in the O-H and C-H vibrational frequency regions is yet to be correlated to the structure of cellulose, these results provided new spectroscopic methods and opportunities to classify and understand the basic crystalline structure, as well as variations, in polymorphism of the crystalline cellulose structure.« less

Evaluation techniques and metrics for assessment of pan+MSI fusion (pansharpening)

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

2015-05-01

Fusion of broadband panchromatic data with narrow band multispectral data - pansharpening - is a common and often studied problem in remote sensing. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. This study examines the output products of 4 commercial implementations with regard to their relative strengths and weaknesses for a set of defined image characteristics and analyst use-cases. Image characteristics used are spatial detail, spatial quality, spectral integrity, and composite color quality (hue and saturation), and analyst use-cases included a variety of object detection and identification tasks. The imagery comes courtesy of the RIT SHARE 2012 collect. Two approaches are used to evaluate the pansharpening methods, analyst evaluation or qualitative measure and image quality metrics or quantitative measures. Visual analyst evaluation results are compared with metric results to determine which metrics best measure the defined image characteristics and product use-cases and to support future rigorous characterization the metrics' correlation with the analyst results. Because pansharpening represents a trade between adding spatial information from the panchromatic image, and retaining spectral information from the MSI channels, the metrics examined are grouped into spatial improvement metrics and spectral preservation metrics. A single metric to quantify the quality of a pansharpening method would necessarily be a combination of weighted spatial and spectral metrics based on the importance of various spatial and spectral characteristics for the primary task of interest. Appropriate metrics and weights for such a combined metric are proposed here, based on the conducted analyst evaluation. Additionally, during this work, a metric was developed specifically focused on assessment of spatial structure improvement relative to a reference image and independent of scene content. Using analysis of Fourier transform images, a measure of high-frequency content is computed in small sub-segments of the image. The average increase in high-frequency content across the image is used as the metric, where averaging across sub-segments combats the scene dependent nature of typical image sharpness techniques. This metric had an improved range of scores, better representing difference in the test set than other common spatial structure metrics.

Power and spectrally efficient M-ARY QAM schemes for future mobile satellite communications

NASA Technical Reports Server (NTRS)

Sreenath, K.; Feher, K.

1990-01-01

An effective method to compensate nonlinear phase distortion caused by the mobile amplifier is proposed. As a first step towards the future use of spectrally efficient modulation schemes for mobile satellite applications, we have investigated effects of nonlinearities and the phase compensation method on 16-QAM. The new method provides about 2 dB savings in power for 16-QAM operation with cost effective amplifiers near saturation and thereby promising use of spectrally efficient linear modulation schemes for future mobile satellite applications.

Entropy Stable Spectral Collocation Schemes for the Navier-Stokes Equations: Discontinuous Interfaces

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Fisher, Travis C.; Nielsen, Eric J.; Frankel, Steven H.

2013-01-01

Nonlinear entropy stability and a summation-by-parts framework are used to derive provably stable, polynomial-based spectral collocation methods of arbitrary order. The new methods are closely related to discontinuous Galerkin spectral collocation methods commonly known as DGFEM, but exhibit a more general entropy stability property. Although the new schemes are applicable to a broad class of linear and nonlinear conservation laws, emphasis herein is placed on the entropy stability of the compressible Navier-Stokes equations.

Reliable noninvasive measurement of blood gases

DOEpatents

Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.; Alam, Mary K.

1994-01-01

Methods and apparatus for, preferably, determining noninvasively and in vivo at least two of the five blood gas parameters (i.e., pH, PCO.sub.2, [HCO.sub.3.sup.- ], PO.sub.2, and O.sub.2 sat.) in a human. The non-invasive method includes the steps of: generating light at three or more different wavelengths in the range of 500 nm to 2500 nm; irradiating blood containing tissue; measuring the intensities of the wavelengths emerging from the blood containing tissue to obtain a set of at least three spectral intensities v. wavelengths; and determining the unknown values of at least two of pH, [HCO.sub.3.sup.- ], PCO.sub.2 and a measure of oxygen concentration. The determined values are within the physiological ranges observed in blood containing tissue. The method also includes the steps of providing calibration samples, determining if the spectral intensities v. wavelengths from the tissue represents an outlier, and determining if any of the calibration samples represents an outlier. The determination of the unknown values is performed by at least one multivariate algorithm using two or more variables and at least one calibration model. Preferably, there is a separate calibration for each blood gas parameter being determined. The method can be utilized in a pulse mode and can also be used invasively. The apparatus includes a tissue positioning device, a source, at least one detector, electronics, a microprocessor, memory, and apparatus for indicating the determined values.

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Method for estimating effects of unknown correlations in spectral irradiance data on uncertainties of spectrally integrated colorimetric quantities

NASA Astrophysics Data System (ADS)

Kärhä, Petri; Vaskuri, Anna; Mäntynen, Henrik; Mikkonen, Nikke; Ikonen, Erkki

2017-08-01

Spectral irradiance data are often used to calculate colorimetric properties, such as color coordinates and color temperatures of light sources by integration. The spectral data may contain unknown correlations that should be accounted for in the uncertainty estimation. We propose a new method for estimating uncertainties in such cases. The method goes through all possible scenarios of deviations using Monte Carlo analysis. Varying spectral error functions are produced by combining spectral base functions, and the distorted spectra are used to calculate the colorimetric quantities. Standard deviations of the colorimetric quantities at different scenarios give uncertainties assuming no correlations, uncertainties assuming full correlation, and uncertainties for an unfavorable case of unknown correlations, which turn out to be a significant source of uncertainty. With 1% standard uncertainty in spectral irradiance, the expanded uncertainty of the correlated color temperature of a source corresponding to the CIE Standard Illuminant A may reach as high as 37.2 K in unfavorable conditions, when calculations assuming full correlation give zero uncertainty, and calculations assuming no correlations yield the expanded uncertainties of 5.6 K and 12.1 K, with wavelength steps of 1 nm and 5 nm used in spectral integrations, respectively. We also show that there is an absolute limit of 60.2 K in the error of the correlated color temperature for Standard Illuminant A when assuming 1% standard uncertainty in the spectral irradiance. A comparison of our uncorrelated uncertainties with those obtained using analytical methods by other research groups shows good agreement. We re-estimated the uncertainties for the colorimetric properties of our 1 kW photometric standard lamps using the new method. The revised uncertainty of color temperature is a factor of 2.5 higher than the uncertainty assuming no correlations.

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.

A fast numerical solution of scattering by a cylinder: Spectral method for the boundary integral equations

NASA Technical Reports Server (NTRS)

Hu, Fang Q.

1994-01-01

It is known that the exact analytic solutions of wave scattering by a circular cylinder, when they exist, are not in a closed form but in infinite series which converges slowly for high frequency waves. In this paper, we present a fast number solution for the scattering problem in which the boundary integral equations, reformulated from the Helmholtz equation, are solved using a Fourier spectral method. It is shown that the special geometry considered here allows the implementation of the spectral method to be simple and very efficient. The present method differs from previous approaches in that the singularities of the integral kernels are removed and dealt with accurately. The proposed method preserves the spectral accuracy and is shown to have an exponential rate of convergence. Aspects of efficient implementation using FFT are discussed. Moreover, the boundary integral equations of combined single and double-layer representation are used in the present paper. This ensures the uniqueness of the numerical solution for the scattering problem at all frequencies. Although a strongly singular kernel is encountered for the Neumann boundary conditions, we show that the hypersingularity can be handled easily in the spectral method. Numerical examples that demonstrate the validity of the method are also presented.

Hyperspectral imaging for predicting the allicin and soluble solid content of garlic with variable selection algorithms and chemometric models.

PubMed

Rahman, Anisur; Faqeerzada, Mohammad A; Cho, Byoung-Kwan

2018-03-14

Allicin and soluble solid content (SSC) in garlic is the responsible for its pungent flavor and odor. However, current conventional methods such as the use of high-pressure liquid chromatography and a refractometer have critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to predict allicin and SSC in garlic using hyperspectral imaging in combination with variable selection algorithms and calibration models. Hyperspectral images of 100 garlic cloves were acquired that covered two spectral ranges, from which the mean spectra of each clove were extracted. The calibration models included partial least squares (PLS) and least squares-support vector machine (LS-SVM) regression, as well as different spectral pre-processing techniques, from which the highest performing spectral preprocessing technique and spectral range were selected. Then, variable selection methods, such as regression coefficients, variable importance in projection (VIP) and the successive projections algorithm (SPA), were evaluated for the selection of effective wavelengths (EWs). Furthermore, PLS and LS-SVM regression methods were applied to quantitatively predict the quality attributes of garlic using the selected EWs. Of the established models, the SPA-LS-SVM model obtained an Rpred2 of 0.90 and standard error of prediction (SEP) of 1.01% for SSC prediction, whereas the VIP-LS-SVM model produced the best result with an Rpred2 of 0.83 and SEP of 0.19 mg g -1 for allicin prediction in the range 1000-1700 nm. Furthermore, chemical images of garlic were developed using the best predictive model to facilitate visualization of the spatial distributions of allicin and SSC. The present study clearly demonstrates that hyperspectral imaging combined with an appropriate chemometrics method can potentially be employed as a fast, non-invasive method to predict the allicin and SSC in garlic. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Spectral characterization of natural backgrounds

NASA Astrophysics Data System (ADS)

Winkelmann, Max

2017-10-01

As the distribution and use of hyperspectral sensors is constantly increasing, the exploitation of spectral features is a threat for camouflaged objects. To improve camouflage materials at first the spectral behavior of backgrounds has to be known to adjust and optimize the spectral reflectance of camouflage materials. In an international effort, the NATO CSO working group SCI-295 "Development of Methods for Measurements and Evaluation of Natural Background EO Signatures" is developing a method how this characterization of backgrounds has to be done. It is obvious that the spectral characterization of a background will be quite an effort. To compare and exchange data internationally the measurements will have to be done in a similar way. To test and further improve this method an international field trial has been performed in Storkow, Germany. In the following we present first impressions and lessons learned from this field campaign and describe the data that has been measured.

Spectral irradiance standard for the ultraviolet - The deuterium lamp

NASA Technical Reports Server (NTRS)

Saunders, R. D.; Ott, W. R.; Bridges, J. M.

1978-01-01

A set of deuterium lamps is calibrated as spectral irradiance standards in the 200-350-nm spectral region utilizing both a high accuracy tungsten spectral irradiance standard and a newly developed argon mini-arc spectral radiance standard. The method which enables a transfer from a spectral radiance to a spectral irradiance standard is described. The following characteristics of the deuterium lamp irradiance standard are determined: sensitivity to alignment; dependence on input power and solid angle; reproducibility; and stability. The absolute spectral radiance is also measured in the 167-330-nm region. Based upon these measurements, values of the spectral irradiance below 200 nm are obtained through extrapolation.

Fourier Transform Spectrometer System

NASA Technical Reports Server (NTRS)

Campbell, Joel F. (Inventor)

2014-01-01

A Fourier transform spectrometer (FTS) data acquisition system includes an FTS spectrometer that receives a spectral signal and a laser signal. The system further includes a wideband detector, which is in communication with the FTS spectrometer and receives the spectral signal and laser signal from the FTS spectrometer. The wideband detector produces a composite signal comprising the laser signal and the spectral signal. The system further comprises a converter in communication with the wideband detector to receive and digitize the composite signal. The system further includes a signal processing unit that receives the composite signal from the converter. The signal processing unit further filters the laser signal and the spectral signal from the composite signal and demodulates the laser signal, to produce velocity corrected spectral data.

Microvolt T-Wave Alternans

PubMed Central

Verrier, Richard L.; Klingenheben, Thomas; Malik, Marek; El-Sherif, Nabil; Exner, Derek V.; Hohnloser, Stefan H.; Ikeda, Takanori; Martínez, Juan Pablo; Narayan, Sanjiv M.; Nieminen, Tuomo; Rosenbaum, David S.

2014-01-01

This consensus guideline was prepared on behalf of the International Society for Holter and Noninvasive Electrocardiology and is cosponsored by the Japanese Circulation Society, the Computers in Cardiology Working Group on e-Cardiology of the European Society of Cardiology, and the European Cardiac Arrhythmia Society. It discusses the electrocardiographic phenomenon of T-wave alternans (TWA) (i.e., a beat-to-beat alternation in the morphology and amplitude of the ST- segment or T-wave). This statement focuses on its physiological basis and measurement technologies and its clinical utility in stratifying risk for life-threatening ventricular arrhythmias. Signal processing techniques including the frequency-domain Spectral Method and the time-domain Modified Moving Average method have demonstrated the utility of TWA in arrhythmia risk stratification in prospective studies in >12,000 patients. The majority of exercise-based studies using both methods have reported high relative risks for cardiovascular mortality and for sudden cardiac death in patients with preserved as well as depressed left ventricular ejection fraction. Studies with ambulatory electrocardiogram-based TWA analysis with Modified Moving Average method have yielded significant predictive capacity. However, negative studies with the Spectral Method have also appeared, including 2 interventional studies in patients with implantable defibrillators. Meta-analyses have been performed to gain insights into this issue. Frontiers of TWA research include use in arrhythmia risk stratification of individuals with preserved ejection fraction, improvements in predictivity with quantitative analysis, and utility in guiding medical as well as device-based therapy. Overall, although TWA appears to be a useful marker of risk for arrhythmic and cardiovascular death, there is as yet no definitive evidence that it can guide therapy. PMID:21920259

Optical remote sensing for forest area estimation

Treesearch

Randolph H. Wynne; Richard G. Oderwald; Gregory A. Reams; John A. Scrivani

2000-01-01

The air photo dot-count method is now widely and successfully used for estimating operational forest area in the USDA Forest Inventory and Analysis (FIA) program. Possible alternatives that would provide for more frequent updates, spectral change detection, and maps of forest area include the AVHRR calibration center technique and various Landsat TM classification...

Principal Component Analysis: Resources for an Essential Application of Linear Algebra

ERIC Educational Resources Information Center

Pankavich, Stephen; Swanson, Rebecca

2015-01-01

Principal Component Analysis (PCA) is a highly useful topic within an introductory Linear Algebra course, especially since it can be used to incorporate a number of applied projects. This method represents an essential application and extension of the Spectral Theorem and is commonly used within a variety of fields, including statistics,…

A Thermal Infrared Radiation Parameterization for Atmospheric Studies

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Suarez, Max J.; Liang, Xin-Zhong; Yan, Michael M.-H.; Cote, Charles (Technical Monitor)

2001-01-01

This technical memorandum documents the longwave radiation parameterization developed at the Climate and Radiation Branch, NASA Goddard Space Flight Center, for a wide variety of weather and climate applications. Based on the 1996-version of the Air Force Geophysical Laboratory HITRAN data, the parameterization includes the absorption due to major gaseous absorption (water vapor, CO2, O3) and most of the minor trace gases (N2O, CH4, CFCs), as well as clouds and aerosols. The thermal infrared spectrum is divided into nine bands. To achieve a high degree of accuracy and speed, various approaches of computing the transmission function are applied to different spectral bands and gases. The gaseous transmission function is computed either using the k-distribution method or the table look-up method. To include the effect of scattering due to clouds and aerosols, the optical thickness is scaled by the single-scattering albedo and asymmetry factor. The parameterization can accurately compute fluxes to within 1% of the high spectral-resolution line-by-line calculations. The cooling rate can be accurately computed in the region extending from the surface to the 0.01-hPa level.

Color reproduction of human skin by spectral reflectance using RGB images and the Wiener estimation method

NASA Astrophysics Data System (ADS)

Sato, Kiyomi; Miyazawa, Shota; Funamizu, Hideki; Yuasa, Tomonori; Nishidate, Izumi; Aizu, Yoshihisa

2017-04-01

Skin measurements based on spectral reflectance are widely studied in the fields of medical care and cosmetics. It has the advantage that several skin properties can be estimated in the non-invasive and non-contacting manner. In this study, we demonstrate the color reproduction of human skin by spectral reflectance using RGB images and the Wiener estimation method.

Effects of fabrication methods on spin relaxation and crystallite quality in Tm-doped ? powders studied using spectral hole burning

NASA Astrophysics Data System (ADS)

Lutz, Thomas; Veissier, Lucile; Thiel, Charles W.; Woodburn, Philip J. T.; Cone, Rufus L.; Barclay, Paul E.; Tittel, Wolfgang

2016-01-01

High-quality rare-earth-ion (REI) doped materials are a prerequisite for many applications such as quantum memories, ultra-high-resolution optical spectrum analyzers and information processing. Compared to bulk materials, REI doped powders offer low-cost fabrication and a greater range of accessible material systems. Here we show that crystal properties, such as nuclear spin lifetime, are strongly affected by mechanical treatment, and that spectral hole burning can serve as a sensitive method to characterize the quality of REI doped powders. We focus on the specific case of thulium doped ? (Tm:YAG). Different methods for obtaining the powders are compared and the influence of annealing on the spectroscopic quality of powders is investigated on a few examples. We conclude that annealing can reverse some detrimental effects of powder fabrication and, in certain cases, the properties of the bulk material can be reached. Our results may be applicable to other impurities and other crystals, including color centers in nano-structured diamond.

A spectral domain method for remotely probing stratified media

NASA Technical Reports Server (NTRS)

Schaubert, D. H.; Mittra, R.

1977-01-01

The problem of remotely probing a stratified, lossless, dielectric medium is formulated using the spectral domain method of probing. The response of the medium to a spectrum of plane waves incident at various angles is used to invert the unknown profile. For TE polarization, the electric field satisfies a Helmholtz equation. The inverse problem is solved by means of a new representation for the wave function. The principal step in this inversion is solving a second kind Fredholm equation which is very amenable to numerical computations. Several examples are presented including some which indicate that the method can be used with experimentally obtained data. When the fields exhibit a surface wave behavior, a unique inversion can be obtained only if information about the magnetic field is also available. In this case, the inversion is accomplished by a two-step procedure which employs a formula of Jost and Kohn. Some examples are presented, and an approach which greatly shortens the computations without greatly deteriorating the results is discussed.

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

High-accuracy measurement of low-water-content in liquid using NIR spectral absorption method

NASA Astrophysics Data System (ADS)

Peng, Bao-Jin; Wan, Xu; Jin, Hong-Zhen; Zhao, Yong; Mao, He-Fa

2005-01-01

Water content measurement technologies are very important for quality inspection of food, medicine products, chemical products and many other industry fields. In recent years, requests for accurate low-water-content measurement in liquid are more and more exigent, and great interests have been shown from the research and experimental work. With the development and advancement of modern production and control technologies, more accurate water content technology is needed. In this paper, a novel experimental setup based on near-infrared (NIR) spectral technology and fiber-optic sensor (OFS) is presented. It has a good measurement accuracy about -/+ 0.01%, which is better, to our knowledge, than most other methods published until now. It has a high measurement resolution of 0.001% in the measurement range from zero to 0.05% for water-in-alcohol measurement, and the water-in-oil measurement is carried out as well. In addition, the advantages of this method also include pollution-free to the measured liquid, fast measurement and so on.

PSYCHE Pure Shift NMR Spectroscopy.

PubMed

Foroozandeh, Mohammadali; Morris, Gareth; Nilsson, Mathias

2018-03-13

Broadband homodecoupling techniques in NMR, also known as "pure shift" methods, aim to enhance spectral resolution by suppressing the effects of homonuclear coupling interactions to turn multiplet signals into singlets. Such techniques typically work by selecting a subset of "active" nuclear spins to observe, and selectively inverting the remaining, "passive", spins to reverse the effects of coupling. Pure Shift Yielded by Chirp Excitation (PSYCHE) is one such method; it is relatively recent, but has already been successfully implemented in a range of different NMR experiments. Paradoxically, PSYCHE is one of the trickiest of pure shift NMR techniques to understand but one of the easiest to use. Here we offer some insights into theoretical and practical aspects of the method, and into the effects and importance of the experimental parameters. Some recent improvements that enhance the spectral purity of PSYCHE spectra will be presented, and some experimental frameworks including examples in 1D and 2D NMR spectroscopy, for the implementation of PSYCHE will be introduced. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of the Spectral Element Method to Acoustic Radiation

NASA Technical Reports Server (NTRS)

Doyle, James F.; Rizzi, Stephen A. (Technical Monitor)

2000-01-01

This report summarizes research to develop a capability for analysis of interior noise in enclosed structures when acoustically excited by an external random source. Of particular interest was the application to the study of noise and vibration transmission in thin-walled structures as typified by aircraft fuselages. Three related topics are focused upon. The first concerns the development of a curved frame spectral element, the second shows how the spectral element method for wave propagation in folded plate structures is extended to problems involving curved segmented plates. These are of significance because by combining these curved spectral elements with previously presented flat spectral elements, the dynamic response of geometrically complex structures can be determined. The third topic shows how spectral elements, which incorporate the effect of fluid loading on the structure, are developed for analyzing acoustic radiation from dynamically loaded extended plates.

Application of spectral methods for high-frequency financial data to quantifying states of market participants

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2008-06-01

Empirical analysis of the foreign exchange market is conducted based on methods to quantify similarities among multi-dimensional time series with spectral distances introduced in [A.-H. Sato, Physica A 382 (2007) 258-270]. As a result it is found that the similarities among currency pairs fluctuate with the rotation of the earth, and that the similarities among best quotation rates are associated with those among quotation frequencies. Furthermore, it is shown that the Jensen-Shannon spectral divergence is proportional to a mean of the Kullback-Leibler spectral distance both empirically and numerically. It is confirmed that these spectral distances are connected with distributions for behavioural parameters of the market participants from numerical simulation. This concludes that spectral distances of representative quantities of financial markets are related into diversification of behavioural parameters of the market participants.

Michael Sprague | NREL

Science.gov Websites

student, he developed a parallel spectral finite element method for treating the interaction of large mechanics of fluids, structures, and their interaction|Spectral finite-element methods for time-dependent

A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

NASA Astrophysics Data System (ADS)

Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

2016-11-01

The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

Spatial-spectral blood cell classification with microscopic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ran, Qiong; Chang, Lan; Li, Wei; Xu, Xiaofeng

2017-10-01

Microscopic hyperspectral images provide a new way for blood cell examination. The hyperspectral imagery can greatly facilitate the classification of different blood cells. In this paper, the microscopic hyperspectral images are acquired by connecting the microscope and the hyperspectral imager, and then tested for blood cell classification. For combined use of the spectral and spatial information provided by hyperspectral images, a spatial-spectral classification method is improved from the classical extreme learning machine (ELM) by integrating spatial context into the image classification task with Markov random field (MRF) model. Comparisons are done among ELM, ELM-MRF, support vector machines(SVM) and SVMMRF methods. Results show the spatial-spectral classification methods(ELM-MRF, SVM-MRF) perform better than pixel-based methods(ELM, SVM), and the proposed ELM-MRF has higher precision and show more accurate location of cells.

Accurate spectral solutions for the parabolic and elliptic partial differential equations by the ultraspherical tau method

NASA Astrophysics Data System (ADS)

Doha, E. H.; Abd-Elhameed, W. M.

2005-09-01

We present a double ultraspherical spectral methods that allow the efficient approximate solution for the parabolic partial differential equations in a square subject to the most general inhomogeneous mixed boundary conditions. The differential equations with their boundary and initial conditions are reduced to systems of ordinary differential equations for the time-dependent expansion coefficients. These systems are greatly simplified by using tensor matrix algebra, and are solved by using the step-by-step method. Numerical applications of how to use these methods are described. Numerical results obtained compare favorably with those of the analytical solutions. Accurate double ultraspherical spectral approximations for Poisson's and Helmholtz's equations are also noted. Numerical experiments show that spectral approximation based on Chebyshev polynomials of the first kind is not always better than others based on ultraspherical polynomials.

Irreducible Green's functions method for a quantum dot coupled to metallic and superconducting leads

NASA Astrophysics Data System (ADS)

Górski, Grzegorz; Kucab, Krzysztof

2017-05-01

Using irreducible Green's functions (IGF) method we analyse the Coulomb interaction dependence of the spectral functions and the transport properties of a quantum dot coupled to isotropic superconductor and metallic leads (SC-QD-N). The irreducible Green's functions method is the modification of classical equation of motion technique. The IGF scheme is based on differentiation of double-time Green's functions, both over the primary and secondary times. The IGF method allows to obtain the spectral functions for equilibrium and non-equilibrium impurity Anderson model used for SC-QD-N system. By the numerical computations, we show the change of spectral and the anomalous densities under the influence of the Coulomb interactions. The observed sign change of the anomalous spectral density can be used as the criterion of the SC singlet-Kondo singlet transition.

A method for spectral DNS of low Rm channel flows based on the least dissipative modes

NASA Astrophysics Data System (ADS)

Kornet, Kacper; Pothérat, Alban

2015-10-01

We put forward a new type of spectral method for the direct numerical simulation of flows where anisotropy or very fine boundary layers are present. The main idea is to take advantage of the fact that such structures are dissipative and that their presence should reduce the number of degrees of freedom of the flow, when paradoxically, their fine resolution incurs extra computational cost in most current methods. The principle of this method is to use a functional basis with elements that already include these fine structures so as to avoid these extra costs. This leads us to develop an algorithm to implement a spectral method for arbitrary functional bases, and in particular, non-orthogonal ones. We construct a basic implementation of this algorithm to simulate magnetohydrodynamic (MHD) channel flows with an externally imposed, transverse magnetic field, where very thin boundary layers are known to develop along the channel walls. In this case, the sought functional basis can be built out of the eigenfunctions of the dissipation operator, which incorporate these boundary layers, and it turns out to be non-orthogonal. We validate this new scheme against numerical simulations of freely decaying MHD turbulence based on a finite volume code and it is found to provide accurate results. Its ability to fully resolve wall-bounded turbulence with a number of modes close to that required by the dynamics is demonstrated on a simple example. This opens the way to full-blown simulations of MHD turbulence under very high magnetic fields. Until now such simulations were too computationally expensive. In contrast to traditional methods the computational cost of the proposed method, does not depend on the intensity of the magnetic field.

Stochastic model stationarization by eliminating the periodic term and its effect on time series prediction

NASA Astrophysics Data System (ADS)

Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan

2017-04-01

Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.

Blood characterization using UV/vis spectroscopy

NASA Astrophysics Data System (ADS)

Mattley, Yvette D.; Mitrani-Gold, F.; Orton, S.; Bacon, Christina P.; Leparc, German F.; Bayona, M.; Potter, Robert L.; Garcia-Rubio, Luis H.

1995-05-01

The current methods used for typing blood involve an agglutination reaction which results from the association of specific antibodies with antigens present on the erythrocyte cell surface. While this method is effective, it requires involved laboratory procedures to detect the cell surface antigens. As an alternative technique, uv/vis spectroscopy has been investigated as a novel way to characterize and differentiate the blood types. Typing with this technique is based on spectral differences which appear throughout portions of both the ultraviolet and visible range. The origin of these spectral differences is unknown and presently under investigation. They may be due to intrinsic absorption differences at the molecular level, and/or they may be due to scattering differences brought about by either subtle variation in cell surface characteristics, cell shape or state of aggregation. As the background optical density in these samples is identified and accounted for, the spectral differences become more defined. This work and the continuation of this project will be included in a general database encompassing a wide range of blood samples. In addition, long term goals involve the investigation of diseased blood with the potential of providing a more rapid diagnosis for blood borne pathogens.

Ground-Based Correction of Remote-Sensing Spectral Imagery

NASA Technical Reports Server (NTRS)

Alder-Golden, Steven M.; Rochford, Peter; Matthew, Michael; Berk, Alexander

2007-01-01

Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.

Estimation of Cardiopulmonary Parameters From Ultra Wideband Radar Measurements Using the State Space Method.

PubMed

Naishadham, Krishna; Piou, Jean E; Ren, Lingyun; Fathy, Aly E

2016-12-01

Ultra wideband (UWB) Doppler radar has many biomedical applications, including remote diagnosis of cardiovascular disease, triage and real-time personnel tracking in rescue missions. It uses narrow pulses to probe the human body and detect tiny cardiopulmonary movements by spectral analysis of the backscattered electromagnetic (EM) field. With the help of super-resolution spectral algorithms, UWB radar is capable of increased accuracy for estimating vital signs such as heart and respiration rates in adverse signal-to-noise conditions. A major challenge for biomedical radar systems is detecting the heartbeat of a subject with high accuracy, because of minute thorax motion (less than 0.5 mm) caused by the heartbeat. The problem becomes compounded by EM clutter and noise in the environment. In this paper, we introduce a new algorithm based on the state space method (SSM) for the extraction of cardiac and respiration rates from UWB radar measurements. SSM produces range-dependent system poles that can be classified parametrically with spectral peaks at the cardiac and respiratory frequencies. It is shown that SSM produces accurate estimates of the vital signs without producing harmonics and inter-modulation products that plague signal resolution in widely used FFT spectrograms.

Peripheral transverse densities of the baryon octet from chiral effective field theory and dispersion analysis

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

Alarcón, J. M.; Hiller Blin, A. N.; Vicente Vacas, M. J.

2017-05-08

The baryon electromagnetic form factors are expressed in terms of two-dimensional densities describing the distribution of charge and magnetization in transverse space at fixed light-front time. In this paper, we calculate the transverse densities of the spin-1/2 flavor-octet baryons at peripheral distances b=O(Mmore » $$-1\\atop{π}$$) using methods of relativistic chiral effective field theory (χ EFT) and dispersion analysis. The densities are represented as dispersive integrals over the imaginary parts of the form factors in the timelike region (spectral functions). The isovector spectral functions on the two-pion cut t > 4 M$$2\\atop{π}$$ are calculated using relativistic χEFT including octet and decuplet baryons. The χEFT calculations are extended into the ρ meson mass region using an N/D method that incorporates the pion electromagnetic form factor data. The isoscalar spectral functions are modeled by vector meson poles. We compute the peripheral charge and magnetization densities in the octet baryon states, estimate the uncertainties, and determine the quark flavor decomposition. Finally, the approach can be extended to baryon form factors of other operators and the moments of generalized parton distributions.« less

A spectrally accurate boundary-layer code for infinite swept wings

NASA Technical Reports Server (NTRS)

Pruett, C. David

1994-01-01

This report documents the development, validation, and application of a spectrally accurate boundary-layer code, WINGBL2, which has been designed specifically for use in stability analyses of swept-wing configurations. Currently, we consider only the quasi-three-dimensional case of an infinitely long wing of constant cross section. The effects of streamwise curvature, streamwise pressure gradient, and wall suction and/or blowing are taken into account in the governing equations and boundary conditions. The boundary-layer equations are formulated both for the attachment-line flow and for the evolving boundary layer. The boundary-layer equations are solved by marching in the direction perpendicular to the leading edge, for which high-order (up to fifth) backward differencing techniques are used. In the wall-normal direction, a spectral collocation method, based upon Chebyshev polynomial approximations, is exploited. The accuracy, efficiency, and user-friendliness of WINGBL2 make it well suited for applications to linear stability theory, parabolized stability equation methodology, direct numerical simulation, and large-eddy simulation. The method is validated against existing schemes for three test cases, including incompressible swept Hiemenz flow and Mach 2.4 flow over an airfoil swept at 70 deg to the free stream.

Spectral estimation—What is new? What is next?

NASA Astrophysics Data System (ADS)

Tary, Jean Baptiste; Herrera, Roberto Henry; Han, Jiajun; van der Baan, Mirko

2014-12-01

Spectral estimation, and corresponding time-frequency representation for nonstationary signals, is a cornerstone in geophysical signal processing and interpretation. The last 10-15 years have seen the development of many new high-resolution decompositions that are often fundamentally different from Fourier and wavelet transforms. These conventional techniques, like the short-time Fourier transform and the continuous wavelet transform, show some limitations in terms of resolution (localization) due to the trade-off between time and frequency localizations and smearing due to the finite size of the time series of their template. Well-known techniques, like autoregressive methods and basis pursuit, and recently developed techniques, such as empirical mode decomposition and the synchrosqueezing transform, can achieve higher time-frequency localization due to reduced spectral smearing and leakage. We first review the theory of various established and novel techniques, pointing out their assumptions, adaptability, and expected time-frequency localization. We illustrate their performances on a provided collection of benchmark signals, including a laughing voice, a volcano tremor, a microseismic event, and a global earthquake, with the intention to provide a fair comparison of the pros and cons of each method. Finally, their outcomes are discussed and possible avenues for improvements are proposed.

A novel Pareto-based Bayesian approach on extension of the infogram for extracting repetitive transients

NASA Astrophysics Data System (ADS)

Gu, Xiaohui; Yang, Shaopu; Liu, Yongqiang; Hao, Rujiang

2018-06-01

Two most important signatures of repetitive transients in the vibration signals of a faulty rotating machine are impulsiveness and cyclostationarity. In the newly proposed infogram, the time-domain and frequency-domain spectral negentropy were put forward to characterize these two aspects, respectively. However, in extension of the infogram to Bayesian inference based optimal wavelet filtering, only one spectral negentropy was employed in identifying the informative frequency band. To overcome its drawback, a novel Pareto-based Bayesian approach was proposed in this paper. The Pareto optimal solutions which can simultaneously maximize the time-domain and frequency-domain spectral negentropy were utilized in estimating the posterior wavelet parameters distributions. Moreover, the relationship between the impulsive and cyclostationary signatures was established by the domination. It can help balance the contributions due to these two aspects other than simply synthesize by the average weight in the infogram. Three instance studies including simulated and experimental signals were investigated to illustrate the effectiveness of the proposed method by challenging different noises and interferences. In addition, some comparisons with the aforementioned peer methods were also conducted to show its superiority and robustness in extracting the repetitive transients.

A new family of high-order compact upwind difference schemes with good spectral resolution

NASA Astrophysics Data System (ADS)

Zhou, Qiang; Yao, Zhaohui; He, Feng; Shen, M. Y.

2007-12-01

This paper presents a new family of high-order compact upwind difference schemes. Unknowns included in the proposed schemes are not only the values of the function but also those of its first and higher derivatives. Derivative terms in the schemes appear only on the upwind side of the stencil. One can calculate all the first derivatives exactly as one solves explicit schemes when the boundary conditions of the problem are non-periodic. When the proposed schemes are applied to periodic problems, only periodic bi-diagonal matrix inversions or periodic block-bi-diagonal matrix inversions are required. Resolution optimization is used to enhance the spectral representation of the first derivative, and this produces a scheme with the highest spectral accuracy among all known compact schemes. For non-periodic boundary conditions, boundary schemes constructed in virtue of the assistant scheme make the schemes not only possess stability for any selective length scale on every point in the computational domain but also satisfy the principle of optimal resolution. Also, an improved shock-capturing method is developed. Finally, both the effectiveness of the new hybrid method and the accuracy of the proposed schemes are verified by executing four benchmark test cases.

Noninvasive quantitative documentation of cutaneous inflammation in vivo using spectral imaging

NASA Astrophysics Data System (ADS)

Stamatas, Georgios N.; Kollias, Nikiforos

2006-02-01

Skin inflammation is often accompanied by edema and erythema. While erythema is the result of capillary dilation and subsequent local increase of oxygenated hemoglobin (oxy-Hb) concentration, edema is characterized by an increase in extracellular fluid in the dermis leading to local tissue swelling. Edema and erythema are typically graded visually. In this work we tested the potential of spectral imaging as a non-invasive method for quantitative documentation of both the erythema and the edema reactions. As examples of dermatological conditions that exhibit skin inflammation we imaged patients suffering from acne, herpes zoster, and poison ivy rashes using a hyperspectral-imaging camera. Spectral images were acquired in the visible and near infrared part of the spectrum, where oxy-Hb and water demonstrate absorption bands. The values of apparent concentrations of oxy-Hb and water were calculated based on an algorithm that takes into account spectral contributions of deoxy-hemoglobin, melanin, and scattering. In each case examined concentration maps of oxy-Hb and water can be constructed that represent quantitative visualizations of the intensity and extent of erythema and edema correspondingly. In summary, we demonstrate that spectral imaging can be used in dermatology to quantitatively document parameters relating to skin inflammation. Applications may include monitoring of disease progression as well as efficacy of treatments.

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.