SAR image change detection based on low rank matrix decomposition

In this paper we propose an unsupervised approach for SAR image change detection task. A new method based on compressed sensing is applied. First using the PPB method for the speckle reduction, and then the logarithm ratio method is applied to generate a simple change map, and then the compressed sensing-based method is used to part the change map into a low rank part and a sparse part, where the sparse part is correspond to the changed area, finally k-means algorithm is applied to cluster the sparse part into two clusters. Experiment results show the effectiveness and feasibility of the proposed method.