Sparse + smooth decomposition models for multi-temporal SAR images

Abstract : SAR images have distinctive characteristics compared to optical images: speckle phenomenon produces strong fluctuations, and strong scatterers have radar signatures several orders of magnitude larger than others. We propose to use an image decomposition approach to account for these peculiarities. Several methods have been proposed in the field of image processing to decompose an image into components of different nature, such as a geometrical part and a textural part. They are generally stated as an energy minimization problem where specific penalty terms are applied to each component of the sought decomposition. We decompose temporal series of SAR images into three components: speckle, strong scatterers and background. Our decomposition method is based on a discrete optimization technique by graph-cut. We apply it to change detection tasks.
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Communication dans un congrès
8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp), Jul 2015, Annecy, France. 2015, 〈10.1109/Multi-Temp.2015.7245772〉
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Sylvain Lobry, Loïc Denis, Florence Tupin. Sparse + smooth decomposition models for multi-temporal SAR images. 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp), Jul 2015, Annecy, France. 2015, 〈10.1109/Multi-Temp.2015.7245772〉. 〈ujm-01219129〉

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