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Article Dans Une Revue IEEE Transactions on Geoscience and Remote Sensing Année : 2013

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

Résumé

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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Dates et versions

hal-00721877 , version 1 (30-07-2012)

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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, 2013, 51 (4), pp. 1922-1938. ⟨10.1109/TGRS.2012.2210228⟩. ⟨hal-00721877⟩
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