Sparsity constraint SAR speckle reduction based on redundant multiscale ridgelet dictionary

Chengzhi Deng; Shengqian Wang

doi:10.1117/12.832421

30 October 2009 Sparsity constraint SAR speckle reduction based on redundant multiscale ridgelet dictionary

Chengzhi Deng, Shengqian Wang

Proceedings Volume 7494, MIPPR 2009: Multispectral Image Acquisition and Processing; 749415 (2009) https://doi.org/10.1117/12.832421
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

In this paper, we proposed a SAR speckle reduction method based on sparse and redundant representations over multiscale ridgelet dictionary. Firstly, the multiscale ridgelet function is proposed. And then based on it, the multiscale ridgelet dictionary is constructed, which can sparsely represent the SAR images. Finally, we propose a global image prior that forces sparsity over small patches in every location in the image. We define a maximum a-posteriori probability (MAP) estimator as the minimizer of a well-defined global penalty term. The speckle reduction leads to a simple iterated patch-by-patch sparse coding and averaging algorithm. The experimental results demonstrate that the proposed method performs better than several other existing methods in terms of quantitative performance as well as in term of visual quality of the images.

Citation Download Citation

Chengzhi Deng and Shengqian Wang "Sparsity constraint SAR speckle reduction based on redundant multiscale ridgelet dictionary", Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 749415 (30 October 2009); https://doi.org/10.1117/12.832421

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