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Proceedings Paper

Shadow-insensitive material detection/classification with atmospherically corrected hyperspectral imagery
Author(s): Steven M. Adler-Golden; Robert Y. Levine; Michael W. Matthew; Steven C. Richtsmeier; Lawrence S. Bernstein; John H. Gruninger; Gerald W. Felde; Michael L. Hoke; Gail P. Anderson; Anthony Ratkowski-
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Paper Abstract

Shadow-insensitive detection or classification of surface materials in atmospherically corrected hyperspectral imagery can be achieved by expressing the reflectance spectrum as a linear combination of spectra that correspond to illumination by the direct sum and by the sky. Some specific algorithms and applications are illustrated using HYperspectral Digital Imagery Collection Experiment (HYDICE) data.

Paper Details

Date Published: 20 August 2001
PDF: 10 pages
Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); doi: 10.1117/12.437037
Show Author Affiliations
Steven M. Adler-Golden, Spectral Sciences, Inc. (United States)
Robert Y. Levine, Spectral Sciences, Inc. (United States)
Michael W. Matthew, Spectral Sciences, Inc. (United States)
Steven C. Richtsmeier, Spectral Sciences, Inc. (United States)
Lawrence S. Bernstein, Spectral Sciences, Inc. (United States)
John H. Gruninger, Spectral Sciences, Inc. (United States)
Gerald W. Felde, Air Force Research Lab. (United States)
Michael L. Hoke, Air Force Research Lab. (United States)
Gail P. Anderson, Air Force Research Lab. (United States)
Anthony Ratkowski-, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 4381:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII
Sylvia S. Shen; Michael R. Descour, Editor(s)

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