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Proceedings Paper

Multi-temporal anomaly detection technique
Author(s): I. Dayan; S. Maman; D. G. Blumberg; S. Rotman
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Paper Abstract

In this paper, we present a variation on the LRX (Local RX) algorithm for detecting anomalies in multi-temporal images. Our algorithm assigns a relative weight to the Mahalanobis distance according to the number of times it appears in an image. Standard transitions between pixels are therefore not viewed as anomalous; unusual transitions are assigned proportionally higher weights. Experimental results using our proposed algorithm vs previous algorithms on multitemporal datasets show a significant improvement.

Paper Details

Date Published: 21 October 2016
PDF: 11 pages
Proc. SPIE 9987, Electro-Optical and Infrared Systems: Technology and Applications XIII, 99870G (21 October 2016); doi: 10.1117/12.2239530
Show Author Affiliations
I. Dayan, Ben-Gurion Univ. of the Negev (Israel)
S. Maman, Ben-Gurion Univ. of the Negev (Israel)
D. G. Blumberg, Ben-Gurion Univ. of the Negev (Israel)
S. Rotman, Ben-Gurion Univ. of the Negev (Israel)


Published in SPIE Proceedings Vol. 9987:
Electro-Optical and Infrared Systems: Technology and Applications XIII
David A. Huckridge; Reinhard Ebert; Stephen T. Lee, Editor(s)

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