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Multiplicative Noise Removal via Nonlocal Similarity-Based Sparse Representation

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Abstract

Based on the sparse representation and by connecting the local and nonlocal regularizer, we proposed a new model to remove multiplicative noise in this paper. We first translated the multiplicative noise into additive noise by a logarithmic transformation, and then introduced a local regularizer based on dictionary learning and a nonlocal regularizer with nonlocal similarity to capture texture and edge information. A surrogate function-based iterative shrinkage algorithm was designed to solve the proposed model. Finally, the solution was transformed back into the real domain via an exponential function and bias correction. Experiments show that the denoised results of our model outperform state-of-the-art algorithms in terms of objective indices and subjective visual effect.

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Acknowledgments

The authors would like to thank the anonymous reviewers for their pertinent and constructive comments. This project was supported in part by the National Natural Science Foundation of China (61362021), in part by Guangxi Natural Science Foundation (2012GXSFBA053014, 2013GXNSFDA019030, 2014GXNSFDA118035), in part by Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics (GIIP201408), and in part by Program for Innovative Research Team of Guilin University of Electronic Technology.

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Authors and Affiliations

  1. School of Mathematics and Computing Science, Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, Guilin University of Electronic Technology, Guilin, China

    Lixia Chen, Xujiao Liu & Pingfang Zhu

  2. Guangxi Experiment Center of Information Science, Guilin, China

    Lixia Chen & Xuewen Wang

  3. Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics, Guilin University of Electronic Technology, Guilin, China

    Lixia Chen & Xuewen Wang

  4. School of Computer Science and Engineering, Guilin University of Electronic Technology, Guilin, China

    Xuewen Wang

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  1. Lixia Chen
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  2. Xujiao Liu
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  4. Pingfang Zhu
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Correspondence to Lixia Chen.

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Chen, L., Liu, X., Wang, X. et al. Multiplicative Noise Removal via Nonlocal Similarity-Based Sparse Representation. J Math Imaging Vis 54, 199–215 (2016). https://doi.org/10.1007/s10851-015-0597-5

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  • DOI: https://doi.org/10.1007/s10851-015-0597-5

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