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Proceedings Paper

Anomaly and target detection by means of nonparametric density estimation
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Paper Abstract

We describe a novel completely non parametric high-dimension joint density estimation algorithm suited for anomaly and target detection using hyperspectral imaging. The new algorithm is compared against linear matched filter detection schemes with different available sample sizes, background statistics (MVN, GMM and non Gaussian). The new algorithm is shown to be superior in important cases.

Paper Details

Date Published: 24 May 2012
PDF: 12 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839020 (24 May 2012); doi: 10.1117/12.919638
Show Author Affiliations
G. A. Tidhar, Ben-Gurion Univ. of the Negev (Israel)
S. R. Rotman, Ben-Gurion Univ. of the Negev (Israel)


Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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