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Multi-temporal SAR classification according to change detection operators

  • Sofiane Hachicha
  • , Charles Alban Deledalle
  • , Ferdaous Chaabane
  • , Florence Tupin
  • University of Carthage, Ecole Supérieure des Communications de Tunis
  • CNRS LTCI

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Citations (Scopus)

Abstract

Multitemporal SAR images are a very useful source of information for geophysicists, especially for change monitoring. In this paper, a new SAR change detection and monitoring approach is proposed through the analysis of a time series of SAR images covering the same region. The first contribution of this work is the SAR filtering preprocessing step using an extension of the spatial NL-means filter to the temporal domain. Then, the Rayleigh Kullback Leibler measure is used to detect the changes between a reference image and each SAR image. This leads to the second contribution which consists on a temporal classification based on changes images and describing the temporal behaviour of the changing regions.

Original languageEnglish
Title of host publication2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings
Pages133-136
Number of pages4
DOIs
Publication statusPublished - 28 Sept 2011
Externally publishedYes
Event2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Trento, Italy
Duration: 12 Jul 2011 → 14 Jul 2011

Publication series

Name2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings

Conference

Conference2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011
Country/TerritoryItaly
CityTrento
Period12/07/11 → 14/07/11

Keywords

  • K-means
  • NL-means
  • Rayleigh Kullback-Leibler
  • Synthetic Aperture Radar

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