SAR images filtering via sparse optimization
SAR图像稀疏优化滤波

In this paper,a new method for filtering SAR images using sparse optimization model is proposed. The algorithm based on sparse representation via an over-complete dictionary has a strong data sparseness and provides solid modeling assumptions for the data sets. First,a sparse optimization model based on structural properties of then SAR image is built by regulation. Second,a practical optimization strategy is used to design a redundancy dictionary. Then,an over-complete dictionary is constructed by employing a combined dictionary consisting of wavelets,shearlets,and a redundancy dictionary. Finally,the filtering process is realized through the solution of the multi-objective optimization problem in which the mean backscatter power is reconstructed. The experimental results demonstrate that the proposed algorithm has good de-speckling capability and better enhances image details.