Structure Preserving SAR Image Despeckling via L0-Minimization

In this paper, we propose a new method for synthetic aperture radar (SAR) image despeckling via L0-minimization strategy, which aims to smooth homogeneous areas while preserve signiflcant structures in SAR images. We argue that the gradients of the despeckled images are sparse and can be pursued by L0-norm minimization. We then formularize the despeckling of SAR images as a global L0 optimization problem with difierence of average operations. Namely, the number of pixels with difierence of average that are unequal to one is controlled to approximate prominent structures in a sparsity-control manner. Finally, a numerical algorithm is employed to solve the L0 minimization problem. In contrast with existing SAR image despeckling approaches, this strategy is applied without necessity to consider the local features or structures. The performance of our method is tested on high-resolution X-band SAR images. The experimental results show that the proposed method achieves state-of- the-art results in terms of the equivalent-number-of-looks measure and the edge-preserving index.