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

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Algorithm development with on-board and ground-based components for hyperspectral gas detection from small satellites 25

Algorithm development with on-board and ground-based compone...

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25th SPIE conference on algorithms, Technologies, and Applications for multispectral and hyperspectral imagery

作者： Theiler, James Love, Steven P. Los Alamos Natl Lab Intelligence & Space Res Div Los Alamos NM 87545 USA

ISBN: (纸本)9781510626386

Los Alamos is currently working toward demonstrating Cubesat-based hyperspectral detection of gas-phase chemical plumes, a goal initially pursued in the internally funded Targeted Atmospheric Chemistry Observations from Space (TACOS) project, and now advancing toward space deployment with the NASA-funded Nanosat Atmospheric Chemistry hyperspectral Observation System (NACHOS). This paper will present a general overview of these projects. Bandwidth considerations prevent full datacube downloads, and so processing algorithms include an on-board processing component to provide matched-filter and RX images for the gases of interest. The downlinked data will additionally include the full spectrum for a small sample of pixels, and one of the challenges for ground-based analysis will be to incorporate these different but incomplete \views" of the datacube into a more physical interpretation/analysis of the downlinked data.

关键词： cubesat satellite hyperspectral imagery algorithm plume detection sparse matrix transform Mahalanobis distance matched filter adaptive coherence estimator

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Sparse linear filters for detection and classification in hyperspectral imagery

Sparse linear filters for detection and classification in hy...

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

作者： Theiler, James Glocer, Karen Los Alamos Natl Lab Space & Remote Sensing Sci Grp Los Alamos NM USA

ISBN: (纸本)0819462896

We investigate the use of convex optimization to identify sparse linear filters in hyperspectral. imagery. A linear filter is sparse if a large fraction of its coefficients are zero. A sparse linear filter can be advantageous because it only needs to access a subset of the available spectral channels, and it can be applied to high-dimensional data more cheaply than a standard linear detector. Finding good sparse filters is nontrivial because there is a combinatorially large number of discrete possibilities from which to choose the optimal subset of nonzero coefficients. But, by converting the optimality criterion into a convex loss function, and by employing an L1 penalty, one can obtain sparse solutions that are globally optimal. We investigate the performance of these sparse filters as a function of their sparsity, and compare the convex optimization approach with more traditional alternatives for feature selection. The methodology is applied both to the adaptive matched filter for weak signal detection, and to the Fisher linear discriminant for terrain categorization.

关键词： matched filter hyperspectral imagery adaptive signal detection

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Atmospheric correction of spectral imagery: evaluation of the FLAASH algorithm with AVIRIS data

Atmospheric correction of spectral imagery: evaluation of th...

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

作者： Matthew, MW Adler-Golden, SM Berk, A Felde, G Anderson, GP Gorodetzky, D Paswaters, S Shippert, M Spectral Sci Inc Burlington MA USA

ISBN: (纸本)0819449539

With its combination of good spatial and spectral resolution, visible to near infrared spectral imaging from aircraft or spacecraft is a highly valuable technology for remote sensing of the earth's surface. Typically it is desirable to eliminate atmospheric effects on the imagery, a process known as atmospheric correction. In this paper we review the basic methodology of first-principles atmospheric correction and present results from the latest version of the FLAASH (Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes) algorithm. We show some comparisons of ground truth spectra with FLAASH-processed AVIRIS data, including results obtained using different processing options, and with results from the ACORN algorithm that derive from an older MODTRAN4 spectral database.

关键词： atmospheric correction compensation hyperspectral adjacency MODTRAN

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Detecting changes in scenes using autonomous smart cameras

Detecting changes in scenes using autonomous smart cameras

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

作者： Jaenisch, Holger M. Handley, James W. Hicklen, Michael L. Dtech Syst Inc POB 18924 Huntsville AL 35804 USA Axiom Corp Two piedmont Ctr Atlanta GA 30305 USA

ISBN: (纸本)9780819466877

This paper describes a novel smart camera algorithm capable of detecting important changes in scenes. These changes take the form of observed crowd dynamics, group behavior, and mounted and unmounted traffic flow. Using webcarn imagery of a football game, these cameras successfully exhibited scene understanding and detected anomalies without prior training or examples. Our algorithm and results are summarized in this paper.

关键词： smart camera webcam imagery anomaly detection scene understanding change detection crowd dynamics

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hyperspectral chemical plume quantification via background radiance estimation

Hyperspectral chemical plume quantification via background r...

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

作者： Niu, Sidi Golowich, Steven E. Ingle, Vinay K. Manolakis, Dimitris G. Northeastern Univ 360 Huntington Ave Boston MA 02115 USA MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)9780819495341

Existing chemical plume quantification algorithms assume that the off-plume radiance of a pixel containing the plume signal is unobservable. When the problem is limited to a single gas, the off-plume radiance may be estimated from the bands in which the gas absorption is nearly zero. It is then possible to compute the difference between the on- and off-plume radiances and solve for the plume strength from Beer's Law. The major advantage of this proposed method is that the gas strength can be resolved from the radiance difference so that the estimation error remains small for thick plumes.

关键词： hyperspectral imagery narrow-band gas background estimation chemical gaseous agent quantification

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Target detection enhancement using temporal signature propagation

Target detection enhancement using temporal signature propag...

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conference on algorithms for multispectral, hyperspectral, and Ultraspectral imagery VI

作者： Mayer, R Schaum, A SFA Inc Largo MD 20774 USA

ISBN: (纸本)0819436755

Changes in atmospheric conditions and sensor response for successive imaging sessions have limited the use of fixed target hyperspectral libraries to help discriminate targets from cluttered backgrounds. The hyperspectral target signature instability and unpredictability have resulted in a dependence on anomaly detection algorithms in real time surveillance applications. However, the performance of these techniques fails to meet system requirements for many military applications. Our study examines temporal variations in the long-wave infrared spectra of man-made targets and natural backgrounds obtained with the SEBASS (8-12 mu m) imager as part of the Dark HORSE 2 exercise during the HYDRA data collection in November, 1998. We examine the signature information propagated over various time intervals. In addition, the hyperspectral target signatures, taken over various time intervals, are transformed using image-based techniques and compared to those converted with methods based on atmospheric modeling. We show that detection performance can be dramatically improved by exploiting signature information propagated over various time intervals using image-based methods. Implications of this study for target detection enhancement using hyperspectral data derived from multiple flight missions and/or mathematical transformations of hyperspectral target signatures will be discussed.

关键词： automatic target detection algorithms for hyperspectral imagery remote sensing

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Implications of model mismatch and covariance contamination on chemical detection algorithms

Implications of model mismatch and covariance contamination ...

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

作者： Niu, Sidi Golowich, Steven E. Ingle, Vinay K. Manolakis, Dimitris G. Northeastern Univ 360 Huntington Ave Boston MA 02115 USA MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)9780819486226

The detection of gaseous chemical plumes in long-wave infrared hyperspectral images is often accomplished with algorithms derived from linear radiance models, such as the matched filter. While such algorithms can be highly effective, deviations of the physical radiative transfer process from the idealized linear model can reduce performance. In particular, the steering vector employed in the matched filter will never exactly match the observed plume signature, the estimated background covariance matrix will often suffer some contamination by the plume signature, and the plume and background will typically be spatially correlated to some extent. In combination, these effects can be worse than they are individually. In this paper, we systematically vary these factors to study their impact on detection using a data set of synthetic plumes embedded into measured background data.

关键词： hyperspectral imagery adaptive matched filter detector covariance contamination steering vector mismatch

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Parameters selection of morphological scale-space decomposition for hyperspectral images using tensor modeling

Parameters selection of morphological scale-space decomposit...

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

作者： Velasco-Forero, Santiago Angulo, Jesus Mines ParisTech Ctr Morphol Math Fontainebleau France

ISBN: (纸本)9780819481597

Dimensionality reduction (DR) using tensor structures in morphological scale-space decomposition (MSSD) for HSI has been investigated in order to incorporate spatial information in DR. We present results of a comprehensive investigation of two issues underlying DR in MSSD. Firstly, information contained in MSSD is reduced using HOSVD but its nonconvex formulation implicates that in some cases a large number of local solutions can be found. For all experiments, HOSVD always reach an unique global solution in the parameter region suitable to practical applications. Secondly, scale parameters in MSSD are presented in relation to connected components size and the influence of scale parameters in DR and subsequent classification is studied.

关键词： U nsupervised feature extraction mathematical morphology tensor analysis dimensional reduction classification principal component hyperspectral imagery

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The effects of atmospheric compensation upon gaseous plume signatures

The effects of atmospheric compensation upon gaseous plume s...

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

作者： Miller, BL Messinger, DW Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Digital Imaging & Remote Sensing Lab Rochester NY 14623 USA

ISBN: (纸本)0819457914

The usual first step in the processing of hyperspectral imagery is to remove the effects of the atmosphere. In the thermal region this usually involves accounting only for the upwelling radiance and the atmospheric transmission: the downwelling contribution being ignorable. This however can cause difficulties in the quantification of the gases if the atmosphere is improperly compensated for. Several algorithms exist for the compensation of the atmosphere including In-scene Atmospheric Compensation (ISAC) and Autonomous Atmospheric Correction (AAC). This study looks at which atmospheric compensation technique., if any, has the least negative impact on the gas signatures in the LWIR region (8-12 microns) using synthetic hyperspectral imagery created with the DIRSIG simulation. Two different metrics were used to this end: spectral angle and feature depth. Because the depth of the gas feature is directly related to the gas ' concentration path length and temperature, it proved to be the more telling of the two. Results show that these atmospheric compensation routines have little effect in the strength of the gas features investigated here and, as such, atmospheric compensation may not be necessary.

关键词： gas plumes hyperspectral imagery atmospheric compensation AAC ISAC DIRSIG

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Automatic estimation of volcanic ash plume height using WorldView-2 imagery

Automatic estimation of volcanic ash plume height using Worl...

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Annual conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XViiI

作者： McLaren, David Thompson, David R. Davies, Ashley G. Gudmundsson, Magnus T. Chien, Steve CALTECH Jet Prop Lab 4800 Oak Grove Dr Pasadena CA 91109 USA Univ Iceland IS-101 Reykjavik Iceland

ISBN: (纸本)9780819490681

We explore the use of machine learning, computer vision, and pattern recognition techniques to automatically identify volcanic ash plumes and plume shadows, in WorldView-2 imagery. Using information of the relative position of the sun and spacecraft and terrain information in the form of a digital elevation map, classification, the height of the ash plume can also be inferred. We present the results from applying this approach to six scenes acquired on two separate days in April and May of 2010 of the Eyjafjallajokull eruption in Iceland. These results show rough agreement with ash plume height estimates from visual and radar based measurements.

关键词： sensorweb volcanoes volcanic ash machine learning computer vision pattern recognition WorldView-2 multispectral

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