Multi-Temporal anomaly detection technique Conference Paper uri icon


  • 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.

publication date

  • January 1, 2016