Release Time:2019-03-10  Hits:

Indexed by: Conference Paper

Date of Publication: 2016-07-10

Included Journals: Scopus、CPCI-S、EI

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.