Paper
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 +
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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Cited by 22 scholarly publications and 1 patent.
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KEYWORDS
Roads

Reflectivity

Sun

Hyperspectral imaging

Atmospheric sensing

Atmospheric corrections

Detection and tracking algorithms

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