@inproceedings{90e5d59d6a7f4fcd925b79e4b684dd22,
title = "Multi-Temporal anomaly detection technique",
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.",
keywords = "LRX, Multi-Temporal, RX, WRX, anomaly, detection",
author = "I. Dayan and S. Maman and Blumberg, {D. G.} and S. Rotman",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Electro-Optical and Infrared Systems: Technology and Applications XIII ; Conference date: 28-09-2016 Through 29-09-2016",
year = "2016",
month = jan,
day = "1",
doi = "10.1117/12.2239530",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Huckridge, {David A.} and Lee, {Stephen T.} and Reinhard Ebert",
booktitle = "Electro-Optical and Infrared Systems",
address = "United States",
}