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Open AccessArticle

Speckle Suppression Based on Sparse Representation with Non-Local Priors

by Shuaiqi Liu 1,2,3,*, Qi Hu 1,2,3, Pengfei Li 1,2,3, Jie Zhao 1,2,3, Chong Wang 4,5,* and Zhihui Zhu 6
1
College of Electronic and Information Engineering, Hebei University, Baoding 071000, China
2
Machine Vision Engineering Research Center of Hebei Province, Baoding 071000, China
3
Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding 071002, China
4
Institute of Geophysics and Geomatics, China University of Geosciences, Beijing 100083, China
5
Bureau of Economic Geology, University of Texas at Austin, Austin, TX 78713, USA
6
Center for Imaging Science, The Johns Hopkins University, Baltimore, MD 21218, USA
*
Authors to whom correspondence should be addressed.
Remote Sens. 2018, 10(3), 439; https://doi.org/10.3390/rs10030439
Received: 16 January 2018 / Revised: 28 February 2018 / Accepted: 9 March 2018 / Published: 11 March 2018
(This article belongs to the Special Issue Data Restoration and Denoising of Remote Sensing Data)
As speckle seriously restricts the applications of remote sensing images in many fields, the ability to efficiently and effectively suppress speckle in a coherent imaging system is indispensable. In order to overcome the over-smoothing problem caused by the speckle suppression algorithm based on classical sparse representation, we propose a non-local speckle suppression algorithm that combines the non-local prior knowledge of the image into the sparse representation. The proposed algorithm first applies shearlet to sparsely represent the input image. We then incorporate the non-local priors as constraints into the image sparse representation de-noising problem. The denoised image is obtained by utilizing an alternating minimization algorithm to solve the corresponding constrained de-noising problem. The experimental results show that the proposed algorithm can not only significantly remove speckle noise, but also improve the visual effect and retain the texture information of the image better.
Keywords: speckle suppression; sparse representation; non-local prior; shearlet speckle suppression; sparse representation; non-local prior; shearlet
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MDPI and ACS Style

Liu, S.; Hu, Q.; Li, P.; Zhao, J.; Wang, C.; Zhu, Z. Speckle Suppression Based on Sparse Representation with Non-Local Priors. Remote Sens. 2018, 10, 439.

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