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Indexed by:会议论文

Date of Publication:2016-07-10

Included Journals:EI、CPCI-S、Scopus

Volume:2016-November

Page Number:72-75

Key Words:SAR image despeckling; Speckle noises; Low-rank representation; Mahalanobis distance

Abstract:Speckle noises are inherent issues in synthetic aperture radar (SAR) images, which hampers the analysis and interpretation of SAR images. In this paper, we propose an iterative low-rank representation algorithm for SAR image despeckling. The original SAR image is first transformed to the logarithmic image, which is then filtered iteratively by the proposed low-rank representation model. Specifically, in each iteration, similar patches measured by the Mahalanobis distance are collected into a group, and then filtered by the nuclear regularized low-rank representation. Finally, all of the filtered patches are aggregated to form the denoised image. Experimental results demonstrate that the proposed algorithm is able to yield state-of-the-art SAR image despeckling performance.