21 October 2016 Multi-temporal anomaly detection technique
Author Affiliations +
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.
Conference Presentation
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I. Dayan, S. Maman, D. G. Blumberg, S. Rotman, "Multi-temporal anomaly detection technique", Proc. SPIE 9987, Electro-Optical and Infrared Systems: Technology and Applications XIII, 99870G (21 October 2016); doi: 10.1117/12.2239530; https://doi.org/10.1117/12.2239530

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