SVD method for spectral decomposition and classification of ARES data

James J. Lisowski; Christopher A. Cook

doi:10.1117/12.257177

6 November 1996 SVD method for spectral decomposition and classification of ARES data

James J. Lisowski, Christopher A. Cook

Proceedings Volume 2821, Hyperspectral Remote Sensing and Applications; (1996) https://doi.org/10.1117/12.257177
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

Use of the Short/Medium Wavelength InfraRed (S/MWIR) region of the electromagnetic spectrum for Hyperspectral Imaging (HSI) applications is a relatively recent occurrence. Unlike the Visible and Near IR, the S/MWIR region is sensitive to reflected sunlight, thermal and molecular emissions. The singular value decomposition technique, traditionally used for processing HSI data, has been employed to extract features from ARES observations of the Navajo Generating Station at Page, AZ. The results have been compared to more straightforward techniques for identifying narrow band molecular emission features. Ground truth measurements made by the Aerospace Corporation are used to verify the extracted features.

Citation Download Citation

James J. Lisowski and Christopher A. Cook "SVD method for spectral decomposition and classification of ARES data", Proc. SPIE 2821, Hyperspectral Remote Sensing and Applications, (6 November 1996); https://doi.org/10.1117/12.257177

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