Multi-Temporal anomaly detection technique

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publicationElectro-Optical and Infrared Systems
Subtitle of host publicationTechnology and Applications XIII
EditorsDavid A. Huckridge, Stephen T. Lee, Reinhard Ebert
ISBN (Electronic)9781510603783
StatePublished - 1 Jan 2016
EventElectro-Optical and Infrared Systems: Technology and Applications XIII - Edinburgh, United Kingdom
Duration: 28 Sep 201629 Sep 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceElectro-Optical and Infrared Systems: Technology and Applications XIII
Country/TerritoryUnited Kingdom


  • LRX
  • Multi-Temporal
  • RX
  • WRX
  • anomaly
  • detection

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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