SAR images de-speckling algorithm via an adaptive over-complete learning dictionary
自适应超完备字典学习的SAR图像降噪

In this paper,a de-speckling algorithm for SAR images using an adaptive over-complete learning dictionary is proposed.The algorithm is based on sparse representation of SAR images via an over-complete dictionary It has strong data sparseness and provides solid modeling assumptions for data sets.First,a practical optimization strategy based on statistical properties of the speckle noise is used to design a redundant dictionary via an iterative loop.Second,the SAR image is projected into a high dimensional space using the learning dictionary and a sparse representation of the SAR image is obtained.Third,a model for multi-objective optimization problem is built by a regulation method.Finally,the de-noising process is realized through a 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 while preserving image details.