Proceedings Paper
Target detection algorithm in hyperspectral imaging using parametric model| Format | Member Price | Non-Member Price |
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Paper Abstract
A supervised subpixel target detection algorithm based on parametric general linear model using whitening transformation for hyperspectral imaging is developed. Statistical tests are described to assess the performance of the algorithm in comparison with the corresponding classical approach. Numerical results are presented to show that the parametric algorithm using low-order models can adequately represent the classical model.
Paper Details
Date Published: 1 June 2005
PDF: 12 pages
Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.609505
Published in SPIE Proceedings Vol. 5806:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI
Sylvia S. Shen; Paul E. Lewis, Editor(s)
PDF: 12 pages
Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.609505
Show Author Affiliations
Edisanter Lo, Susquehanna Univ. (United States)
Published in SPIE Proceedings Vol. 5806:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI
Sylvia S. Shen; Paul E. Lewis, Editor(s)
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