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A Modified NCSR Algorithm for Image Denoising

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Geo-Spatial Knowledge and Intelligence (GRMSE 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 698))

Abstract

In this paper, a modified nonlocally centralized sparse representation method is introduced, which is suitable for removing both the non-sparse noise and sparse noise such as salt and pepper noise, periodic noise, and mixed noise in particular. In the proposed method the conventional median filtering is embedded in nonlocally centralized sparse representation. The main advantage is that it can attain better performance for various common noise, and significantly superior for mixed noise. The effective and efficient of the proposed method is demonstrated experimentally.

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Acknowledgements

This work has been supported by the Fundamental Research Funds for the Central Universities 3132016220.

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Authors and Affiliations

  1. Department of Mathematics, Dalian Maritime University, Dalian, 116026, China

    Diwei Li, Yunjie Zhang & Xin Liu

Authors
  1. Diwei Li
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  2. Yunjie Zhang
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  3. Xin Liu
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Corresponding author

Correspondence to Diwei Li .

Editor information

Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Hanning Yuan

  2. Beijing Institute of Technology, Beijing, China

    Jing Geng

  3. Wuhan University, Wuhan, China

    Fuling Bian

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© 2017 Springer Nature Singapore Pte Ltd.

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Li, D., Zhang, Y., Liu, X. (2017). A Modified NCSR Algorithm for Image Denoising. In: Yuan, H., Geng, J., Bian, F. (eds) Geo-Spatial Knowledge and Intelligence. GRMSE 2016. Communications in Computer and Information Science, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-10-3966-9_43

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  • DOI: https://doi.org/10.1007/978-981-10-3966-9_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3965-2

  • Online ISBN: 978-981-10-3966-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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