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检索条件"任意字段=Conference on Algorithms for Multispectral and Hyperspectral Imagery II"
408 条 记 录,以下是91-100 订阅
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Generation of remotely sensed reference data using low altitude, high spatial resolution hyperspectral imagery  22
Generation of remotely sensed reference data using low altit...
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22nd SPIE conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXii
作者: Williams, McKay D. van Aardt, Jan Kerekes, John P. Chester F Carlson Ctr Imaging Sci 54 Lomb Mem Dr Rochester NY 14623 USA
Exploitation of imaging spectroscopy (hyperspectral) data using classification and spectral unmixing algorithms is a major research area in remote sensing, with reference data required to assess algorithm performance.... 详细信息
来源: 评论
A Parametric Study of Unsupervised Anomaly Detection Performance in Maritime imagery Using Manifold Learning Techniques  22
A Parametric Study of Unsupervised Anomaly Detection Perform...
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22nd SPIE conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXii
作者: Olson, C. C. Doster, T. Naval Res Lab Opt Sci Div 4555 Overlook Ave SW Washington DC 20375 USA
We investigate the parameters that govern an unsupervised anomaly detection framework that uses nonlinear techniques to learn a better model of the non-anomalous data. A manifold or kernel-based model is learned from ... 详细信息
来源: 评论
A spectral climatology for atmospheric compensation of hyperspectral imagery  22
A spectral climatology for atmospheric compensation of hyper...
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22nd SPIE conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXii
作者: Powell, John H. Resmini, Ronald G. George Mason Univ Coll Sci 4400 Univ Dr Fairfax VA 22030 USA
Most Earth observation hyperspectral imagery (HSI) detection and identification algorithms depend critically upon a robust atmospheric compensation capability to correct for the effects of the atmosphere on the radian... 详细信息
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Spectral BRDF modeling of vehicle signature observations in the VNIR-SWIR  22
Spectral BRDF modeling of vehicle signature observations in ...
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22nd SPIE conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXii
作者: Perkins, T. Adler-Golden, S. Muratov, L. Sundberg, R. Ientilucci, E. Cain, L. Spectral Sci Inc 4 Fourth Ave Burlington MA 01803 USA Rochester Inst Technol Digital Imaging & Remote Sensing Lab Rochester NY 14623 USA US Air Force Res Lab RYAT Wright Patterson AFB OH 45433 USA
hyperspectral imaging (HSI) sensors have the ability to detect and identify objects within a scene based on the distinct attributes of their surface spectral signatures. Many targets of interest, such as vehicles, rep... 详细信息
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Identifying vehicles with VNIR-SWIR hyperspectral imagery: Sources of distinguishability and confusion  21
Identifying vehicles with VNIR-SWIR hyperspectral imagery: S...
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SPIE's 21st Imaging Spectrometry conference
作者: Adler-Golden, Steve Sundberg, Robert Spectral Sci Inc 4 Fourth Ave Burlington MA 01803 USA
multispectral and hyperspectral imaging can facilitate vehicle tracking across a series of images by gathering spectral information that distinguishes the vehicle of interest from confusers. Developing effective algor... 详细信息
来源: 评论
hyperspectral reflectance signature protocol for predicting subsurface bottom reflectance in water: in-situ and analytical methods
Hyperspectral reflectance signature protocol for predicting ...
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conference on Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions
作者: Bostater, Charles R., Jr. Rotkiske, Tyler Oney, Taylor Florida Inst Technol Coll Engn Dept Ocean Engn & Sci Marine Environm Opt Lab 150 West Univ Blvd Melbourne FL 32901 USA Florida Inst Technol Ctr Remote Sensing Coll Engn Dept Ocean Engn & Sci 150 West Univ Blvd Melbourne FL 32901 USA
In-situ measurement of bottom reflectance signatures & bottom features in water are used to test an analytical based irradiance model protocol. Comparisons between predicted and measured bottom reflectance signatu... 详细信息
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Ellipsoids for Anomaly Detection in Remote Sensing imagery  21
Ellipsoids for Anomaly Detection in Remote Sensing Imagery
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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXI
作者: Grosklos, Guen Theiler, James Los Alamos Natl Lab POB 1663 Los Alamos NM 87545 USA
For many target and anomaly detection algorithms, a key step is the estimation of a centroid (relatively easy) and a covariance matrix (somewhat harder) that characterize the background clutter. For a background that ... 详细信息
来源: 评论
An Analysis Task Comparison of Uncorrected vs. Geo-registered Airborne hyperspectral imagery  21
An Analysis Task Comparison of Uncorrected vs. Geo-registere...
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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXI
作者: Sun, Yihang Kerekes, John Rochester Inst Technol Rochester NY 14623 USA
Geo-registration is the task of assigning geospatial coordinates to the pixels of an image and placing them in a geographic coordinate system. However, the process of geo-registration can impair the quality of the ima... 详细信息
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Spatial-Spectral Dimensionality Reduction of hyperspectral imagery with Partial Knowledge of Class Labels  21
Spatial-Spectral Dimensionality Reduction of Hyperspectral I...
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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXI
作者: Cahill, Nathan D. Chew, Selene E. Wenger, Paul S. Rochester Inst Technol Sch Math Sci Ctr Appl & Computat Math Rochester NY 14623 USA
Laplacian Eigenmaps (LE) and Schroedinger Eigenmaps (SE) are effective dimensionality reduction algorithms that are capable of integrating both the spatial and spectral information inherent in a hyperspectral image. I... 详细信息
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SLIC Superpixels for Efficient Graph-Based Dimensionality Reduction of hyperspectral imagery  21
SLIC Superpixels for Efficient Graph-Based Dimensionality Re...
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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery XXI
作者: Zhang, Xuewen Chew, Selene E. Xu, Zhenlin Cahill, Nathan D. Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Rochester NY 14623 USA Rochester Inst Technol Sch Math Sci Ctr Appl & Computat Math Rochester NY 14623 USA
Nonlinear graph-based dimensionality reduction algorithms such as Laplacian Eigenmaps (LE) and Schroedinger Eigenmaps (SE) have been shown to be very effective at yielding low-dimensional representations of hyperspect... 详细信息
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