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

Abdourrahmane Atto 1 Emmanuel Trouvé 1 Yannick Berthoumieu 2 Grégoire Mercier 3, 4
1 LISTIC - Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance
2 IMS - Laboratoire de l'intégration, du matériau au système
3 ITI - Département Image et Traitement Information
4 Lab-STICC - Laboratoire en sciences et technologies de l'information, de la communication et de la connaissance [Brest]
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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Submitted on : Monday, July 30, 2012 - 11:50:00 PM
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UNIV-SAVOIE | CNRS | IMS-BORDEAUX | INSTITUT-TELECOM | LAB-STICC | IMS-BORDEAUX-FUSION | UGA | IMT-ATLANTIQUE | LISTIC

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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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