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Multi-Date Divergence Matrices for the Analysis of SAR Image Time Series

Abstract : The paper provides a spatio-temporal change detection framework for the analysis of image time series. In this framework, the detection of changes in time is addressed at the image level by using a matrix of cross-dissimilarities computed upon wavelet and curvelet image features. This makes possible identifying the acquisitions-of-interest: the acquisitions that exhibit singular behavior with respect to their neighborhood in the time series and those that are representatives of some stationary behavior. These acquisitions-of-interest are compared at the pixel level in order to detect spatial changes characterizing the evolution of the time series. Experiments carried out over ERS and TerraSAR-X time series highlight the relevancy of the approach for analyzing SAR image time series.
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Contributor : Abdourrahmane Mahamane Atto Connect in order to contact the contributor
Submitted on : Monday, July 30, 2012 - 11:50:00 PM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM
Long-term archiving on: : Wednesday, October 31, 2012 - 3:51:01 AM


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Abdourrahmane Atto, Emmanuel Trouvé, Yannick Berthoumieu, Grégoire Mercier. Multi-Date Divergence Matrices for the Analysis of SAR Image Time Series. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2013, 51 (4), pp. 1922-1938. ⟨10.1109/TGRS.2012.2210228⟩. ⟨hal-00721877⟩



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