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Speckle reduction and restoration of synthetic aperture radar data with an adoptive Markov random field model

This paper proposes a novel speckle reduction method that combines an advanced statistical distribution with spatial contextual information for SAR data. The method for despeckling is based on a Markov random field (MRF) that integrates a K-distribution for the SAR data statistics and a Gauss-MRF model for the spatial context. These two pieces of information are combined based on weighted summation of pixel-wise and contextual models. This not only preserves edge information in the image, but also improves signal-to-noise ratio (SNR) of the despeckled data. Experiments on real SAR data demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.