Concurrent SAR images denoising and segmentation based on a novel model of wavelet coefficients

A novel segmentation algorithm for Synthetic Aperture Radar (SAR) images is presented in this paper to improve performance. First, we design a model of wavelet coefficients based on the relativities of the coefficients at different scales to sup press noise. Furthermore, we employ a weight-variant graph cuts-based approach to extract objects from complex back ground. Finally, we compare our proposed algorithms with several segmentation measures on synthetic and real SAR images and the experimental results demonstrate that the pro posed strategies have better performances in speckle suppression and image segmentation compared with other methods.