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An improved classifier is presented by imposing a textural feature to solve the problems of vague initial clustering results, low classification accuracy and unchangeable class number in the iterative classifier, based on H/Alpha decomposition and the complex Wishart distribution for fully polarimetric SAR (Synthetic Aperture Radar) images. First, wavelet transformation is used to extract texture from polarimetric SAR images. Second, an AP (Affinity Propagation) algorithm is applied to createdoi:10.12928/telkomnika.v13i1.1318 fatcat:5tfldkdwtffpvlenzm4lb5357y