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