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Noise Suppression by Discontinuity Indicator Controlled Non-local Means Method

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Abstract

The non-local means (NLM) method and its variances have been proved to be effective for noise suppression. However, the traditional NLM method and its variances cannot guarantee to obtain a global optimum solution owing to a globally fixed bandwidth parameter for the entire image is used when computing similarity weight function. To address this problem, this paper proposes an adaptive NLM method based on a novel discontinuity indicator, which can get a good tradeoff between edge preservation and noise reduction. In our method, a novel discontinuity indicator based on the structure tensor is proposed, which can effectively distinguish edges from noises and smooth regions. Furthermore, the bandwidth parameter is adaptively chosen according to the proposed discontinuity indicator. As a result, the bandwidth parameter depends continuously on the local characteristic of each pixel. Experimental results demonstrate that our proposed method outperforms several mainstream methods.

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Acknowledgments

The authors would like thank the Editor and anonymous reviewers for their helpful comments and constructive suggestions. This work was supported by the National Natural Science Foundation of China (61403081), the Natural Science Foundation of Jiangsu Province (BK20140638, BK20150793).

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Authors and Affiliations

  1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People’s Republic of China

    Weili Zeng

  2. Key Laboratory of Measurement and Control of CSE, School of Automation, Southeast University, Nanjing, 210096, People’s Republic of China

    Yijun Du & Changhui Hu

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  1. Weili Zeng
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  2. Yijun Du
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Correspondence to Weili Zeng.

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Zeng, W., Du, Y. & Hu, C. Noise Suppression by Discontinuity Indicator Controlled Non-local Means Method. Multimed Tools Appl 76, 13239–13253 (2017). https://doi.org/10.1007/s11042-016-3753-z

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  • DOI: https://doi.org/10.1007/s11042-016-3753-z

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