Detection of anomalous activity in hyperspectral imaging: metrics for evaluating algorithms

Gil Sharon; Roee Enbar; Stanley R. Rotman; Dan G. Blumberg; Ariel Schlamm; David Messinger

doi:10.1117/12.915346

9 May 2012 Detection of anomalous activity in hyperspectral imaging: metrics for evaluating algorithms

Gil Sharon, Roee Enbar, Stanley R. Rotman, Dan G. Blumberg, Ariel Schlamm, David Messinger

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 83900D (2012) https://doi.org/10.1117/12.915346
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Gil Sharon, Roee Enbar, Stanley R. Rotman, Dan G. Blumberg, Ariel Schlamm, and David Messinger "Detection of anomalous activity in hyperspectral imaging: metrics for evaluating algorithms", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83900D (9 May 2012); https://doi.org/10.1117/12.915346

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