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检索条件"任意字段=Conference on Algorithms for Multispectral and Hyperspectral Imagery IV"

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Proceedings of SPIE: algorithms for multispectral and hyperspectral imagery iv

Proceedings of SPIE: Algorithms for Multispectral and Hypers...

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algorithms for multispectral and hyperspectral imagery iv

This Volume 3372 of the conference proceedings contains 22 papers. Topics discussed include algorithms for multispectral and hyperspectral imagery, detection and classification, image enhancement and data compression,... 详细信息

关键词： Imaging techniques

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algorithms for multispectral and hyperspectral imagery iv

Algorithms for Multispectral and Hyperspectral Imagery IV

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1998年

作者： Sylvia S Shen Michael R Descour

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Wavelet-based noise reduction in multispectral imagery

Wavelet-based noise reduction in multispectral imagery

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conference on algorithms for multispectral and hyperspectral imagery iv

作者： Basuhail, AA Kozaitis, SP Florida Inst Technol Div Elect & Comp Sci & Engn Melbourne FL 32901 USA

ISBN: (纸本)0819428213

We used a 3-D wavelet-based denoising method to reduce the noise from multispectral imagery. In our approach, we compared denoising of different bands of a multispectral image using a 2-D denoising technique, by which the wavelet coefficients corresponding to each band were denoised independent of each band, and a 3-D denoising technique by which the wavelet coefficients were denoised by involving all bands in thresholding the wavelet coefficients. Due to the high correlation of the multispectral imagery data along the wavelength axis, the noise can be easily reduced by applying the wavelet transform along the wavelength direction. Our results showed that the 3-D denoising approach improved the overall SMI of a noisy multispectral imagery over the 2-D denoising approach, due to the correlation between the different bands.

关键词： denoising three-dimensional wavelet transform multispectral

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Detection in hyperspectral imagery

Detection in hyperspectral imagery

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conference on algorithms for multispectral and hyperspectral imagery iv

作者： Schweizer, SM Moura, JMF Carnegie Mellon Univ ECE Dept Pittsburgh PA 15213 USA

ISBN: (纸本)0819428213

hyperspectral sensors collect hundreds of images in contiguous and narrowly spaced spectral bands. They have the potential to simultaneously provide high spatial and spectral resolution of targets of interest in Automatic Target Detection and Recognition (ATD/R). The price to be paid is the need to process and store an extremely large amount of data in an effective and timely manner. We develop a new implementation of the maximum-likelihood (ML) detector which is both practical and efficient. Our detection is based on a Gauss-Markov Random Field (GMRF) model for the data which avoids the inversion of large data covariance matrices usually encountered in ML-detectors. The paper presents two algorithms to fit the GMRF to the hyperspectral sensor data: an optimal ML estimation algorithm and a suboptimal Least Squares (LS) estimation algorithm. Using the LS-algorithm, we develop the structure of the detector and present estimation results from a real hyperspectral data set.

关键词： hyperspectral Gauss-Markov random field maximum-likelihood detector least squares estimation

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Robust spatial and spectral feature extraction for multispectral and hyperspectral imagery

Robust spatial and spectral feature extraction for multispec...

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conference on algorithms for multispectral and hyperspectral imagery iv

作者： Pinzon, JE Ustin, SL Castaneda, CM Pierce, JF Costick, LA Univ Calif Davis Dept Math Davis CA 95616 USA

ISBN: (纸本)0819428213

We present a hierarchical classification technique that discriminates broad categories of surface materials in terms of ground true features, such as water, vegetation, and soils from spectral information. Subsequently, we further discriminate these materials and extract finer ground features, like chemistries, peculiar to each. The interaction at various scales of the 3D spatial and the spectral domains is decomposed by using wavelet tools to address scale dependencies in the spatial domain, a robust spectral unmixing technique, called Hierarchical Foreground Background Analysis (HFBA) along the spectral axis. HFBA sequentially derives a series of weighting vectors discriminating features at different levels of detection: (1) constituent materials, (2) types within constituents, and (3) chemistries peculiar to each type. Our goal is two-fold. First, we present the combination of HFBA and wavelets as a supervised classification technique validating the categories imposed by the supervised classification, and manifesting clusters which can refine the classification at different scales. Second, we identify spectral redundancies between hyperspectral and multispectral information, studying mixtures at different spatial/spectral resolutions and assess whether targeted features may be extracted as efficiently from multispectral data as they could be from hyperspectral data. Results on AVIRIS and simulated MODIS data illustrate the robustness and effectivity of the technique.

关键词： supervised classification multispectral hyperspectral imagery wavelets non-linear mixture analysis

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Trade-off studies of detection performance versus the number of reflective spectral bands in hyperspectral imagery

Trade-off studies of detection performance versus the number...

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conference on algorithms for multispectral and hyperspectral imagery iv

作者： Haskett, HT Sood, AK Night Vis & Elect Sensors Directorate Ft Belvoir VA 22060 USA

ISBN: (纸本)0819428213

This paper presents (1) trade-off studies of detection performance versus the number of bands using reflective hyperspectral imagery;(2) the quantitative detection performance of various approaches used in automatic target detection. The trade-off studies of detection performance versus the number of bands are based on the Adaptive Peal-Tune Endmember Selection and Clutter Suppression (ARES) algorithm ([1]). The ARES algorithm presents a new concept and approach for spectral-spatial aided/automatic target detection based on the unique characteristics of the spectral signatures produced by the hyperspectral imaging system for remote sensing surveillance and reconnaissance applications. This paper compares the quantitative detection performance based on the ARES algorithm with other automatic target detection approaches. This paper uses the Forest Radiance I database collected with the HYDICE hyperspectral sensor at Aberdeen U. S. Army Proving Ground in Maryland, including scenarios such as targets in the open, with footprint of 1 meter, and at different times of day.

关键词： ATR trade-off hyperspectral spectral bands normalized correlation ARES

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Exploiting an atmospheric model for automated invariant material identification in hyperspectral imagery

Exploiting an atmospheric model for automated invariant mate...

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conference on algorithms for multispectral and hyperspectral imagery iv

作者： Slater, D Healey, G Univ Calif Irvine Comp Vis Lab Irvine CA 92697 USA

ISBN: (纸本)0819428213

The measured spectral radiance signature for a material can vary significantly due to atmospheric conditions and scene geometry. We show using a statistical analysis of a comprehensive physical model that the variation in a material's spectral signature lies in a low-dimensional space. The spectral radiance model includes reflected solar and sky radiation as well as path radiance. Signature variability is introduced by effects such as solar occlusion and variation in the concentrations of atmospheric gases and aerosols. The MODTRAN 3.5 code was employed for computing radiative transfer aspects of the model. Using the new model, we develop a maximum likelihood algorithm for automatic material identification that is invariant to atmospheric conditions and scene geometry. We demonstrate the algorithm for the identification of exposed and concealed material samples in HYDICE imagery.

关键词： hyperspectral HYDICE material identification invariant recognition MODTRAN

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Correcting radiance data for randomly occurring nonuniform illumination of the IFOV of individual detectors in arrays

Correcting radiance data for randomly occurring nonuniform i...

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conference on algorithms for multispectral and hyperspectral imagery iv

作者： Berger, H Bosch, EH Simental, E USA Topog Engn Ctr Alexandria VA 22315 USA

ISBN: (纸本)0819428213

This paper discusses the nonuniform illumination of individual pixels in an array that is intrinsic to the scene viewed, as opposed to turbulence or platform motion as an error source in quantitative imagery. It describes two classes of algorithms to treat this type of problem. It points out that this problem can be viewed as a type of inverse problem with a corresponding integral equation unlike those commonly treated in the literature. One class allows estimation of the spatial variation of radiance within pixels using the single digital number irradiances produced by the measurements of the detectors within their instantaneous-fields-of-view (IFOVs). Usually it is assumed without discussion that the intrapixel radiance distribution is constant. Results are presented showing the improvements obtained by the methods discussed.

关键词： detector array nonuniform illumination radiance spatial variation inverse problem quantitative imagery

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Influence of DEM and BRDF effects on the radiometric signal of satellite imagery

Influence of DEM and BRDF effects on the radiometric signal ...

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conference on algorithms for multispectral and hyperspectral imagery iv

作者： Richter, R DLR German Aerosp Ctr Inst Optoelect D-82234 Wessling Germany

ISBN: (纸本)0819428213

The calculation of ground reflectance imagery from satellite scenes acquired over mountainous terrain depends on a number of factors. Two factors are considered here: the spatial resolution of the Digital Elevation Model (DEM) and bidirectional reflectance (BRDF) effects. Due to the large range of local solar incidence angles in a rugged terrain a strong departure from the isotropic reflectance behavior is often apparent in the imagery. Simple empirical functions are offered to reduce the BRDF influence for the reflectance image product. DEM errors, an inadequate spatial resolution or a small sub-pixel misregistration between an image pixel and the DEM resolution cell lead to reflectance errors. The magnitude of this error is wavelength-dependent. Some typical configurations are investigated to assess the DEM influence.

关键词： atmospheric and topographic correction ATCOR3 model DEM BRDF

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Demonstration of the accuracy of improved resolution hyperspectral imagery

Demonstration of the accuracy of improved resolution hypersp...

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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

作者： Vrabel, J Doraiswamy, P McMurtrey, J Stern, A Imaging Technol Consultants Centreville VA 20120 USA

ISBN: (纸本)0819444758

Numerous researchers have demonstrated the accuracy and utility of improved spatial resolution multispectral imagery by sharpening it with higher spatial resolution panchromatic imagery. A much more limited number of researchers have sharpened hyperspectral imagery with panchromatic imagery. In this research we have developed an algorithm that spatially sharpens specific ranges of hyperspectral bands with spectrally correlated multispectral bands of a higher spatial resolution to improve the spatial resolution of the hyperspectral imagery while maintaining or improving it's spectral fidelity. Preliminary validation of the algorithm has been conducted using a 7m AVIRIS scene of the Maryland Eastern Shore containing corn, soybean, and wheat fields. This data was used to simulate 28m HSI and 7m MSI that were used in the sharpening process. Initial analysis has verified the spectral accuracy of the sharpened data. In the next phase of the study, airborne spectral data from two different sensors will be used in the sharpening process with the results used as input for USDA/ARS crop yield and stress models.

关键词： fusion sharpening imagery hyperspectral multispectral remote sensing

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