Shadow-insensitive material detection/classification with atmospherically corrected hyperspectral imagery

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-

doi:10.1117/12.437037

20 August 2001 Shadow-insensitive material detection/classification with atmospherically corrected hyperspectral imagery

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-

Author Affiliations +

Proceedings Volume 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII; (2001) https://doi.org/10.1117/12.437037
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

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.

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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, and Anthony Ratkowski- "Shadow-insensitive material detection/classification with atmospherically corrected hyperspectral imagery", Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); https://doi.org/10.1117/12.437037

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