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In this work we demonstrate the potentiel of the InSAR coherence in classifying regions threatened by the desertification. We propose to combine features from InSAR amplitude and coherence images into a single 3D space in which every pixel is represented by its three-values vector (master image, slave image, coherence image) then to apply the multichannel Fuzzy C-Means (FCM) clustering algorithm....
Fully polarimetric SAR (POL-SAR) images provide a large amount of information through the four channels HH, VV, HV and VH. They proved to be useful in many applications such as delimiting homogenous areas. Such large amounts of data require robust processing algorithms with minimal supervision and low complexity, especially for classification purposes. Most existing classification algorithms (H/A/alpha...
In this work, we classify the interferometric SAR (InSAR) coherence map into three classes using the Bayes' theorem. The segmentation procedure is performed using a mixture modelling of the coherence map. The multimodal density of the mixture comprises three component functions characterizing different land surface categories (lake, bare soil, urban ...). This work is an ameliorated segmentation approach...
SAR interferometry has a large potential for topographic and geophysical parameters extraction algorithms. The interferometric coherence, derived from the cross-correlation of two complex coregistered SAR images, gives additional information complementary to information contained in the amplitude value of the backscattering coefficient. However, the interferometric phase is considered with less importance...
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