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Proceedings Paper

Hyperspectral outlier detector based on conditional distributions
Author(s): Edisanter Lo
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Paper Abstract

An outlier detection algorithm for hyperspectral imaging based on likelihood ratio test is presented in this article. The null hypothesis tests if a test pixel is from the conditional distribution of the pixel given the background subspace and the alternative hypothesis tests if a test pixel is from the conditional distribution of the pixel given the target subspace. Using principal components for the complementary subspaces, a practical outlier detector is developed and is compared to conventional outlier detectors using a VNIR hyperspectral imagery.

Paper Details

Date Published: 12 May 2010
PDF: 4 pages
Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 769506 (12 May 2010); doi: 10.1117/12.851486
Show Author Affiliations
Edisanter Lo, Susquehanna Univ. (United States)


Published in SPIE Proceedings Vol. 7695:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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