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Proceedings Paper

Detection of anomalous activity in hyperspectral imaging: metrics for evaluating algorithms
Author(s): Gil Sharon; Roee Enbar; Stanley R. Rotman; Dan G. Blumberg; Ariel Schlamm; David Messinger
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Paper Abstract

In this paper, we consider detecting man-made objects in natural images. We segment the image into tiles; we consider a variety of statistical metrics and correlate them to the presence of man-made targets. To quantify the metric, we apply a method of implanting targets and evaluating the resulting ROC (Receiver Operating Characteristic) curves. We rank previously reported algorithms and develop new ones in this paper.

Paper Details

Date Published: 9 May 2012
PDF: 6 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83900D (9 May 2012); doi: 10.1117/12.915346
Show Author Affiliations
Gil Sharon, Ben-Gurion Univ. of the Negev (Israel)
Roee Enbar, Ben-Gurion Univ. of the Negev (Israel)
Stanley R. Rotman, Ben-Gurion Univ. of the Negev (Israel)
Dan G. Blumberg, Ben-Gurion Univ. of the Negev (Israel)
Ariel Schlamm, Rochester Institute of Technology (United States)
David Messinger, Rochester Institute of Technology (United States)


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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