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International Symposium on Cyberspace Safety and Security

CSS 2019: Cyberspace Safety and Security pp 501–510Cite as

An Image Denoising Algorithm Based on Singular Value Decomposition and Non-local Self-similarity

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11983))

Abstract

Image denoising is a basic but important step in image pre-processing, computer vision, and related areas. Based on singular value decomposition (SVD) and non-local self-similarity, This paper proposed an image denoising algorithm which is simple in computation. The proposed algorithm is divided into three steps: firstly, the block matching technique is used to find similar patches to construct one matrix, which is of low rank; secondly, SVD is performed on this matrix, and the singular value matrix is processed by principal component analysis (PCA); finally, all similar patches are aggregated to retrieve the denoised image. Since the noise in the image will affect the computation of similar patches, this procedure is iterated many times to enhance the performance. Simulated experiments on different images show that the proposed algorithm performs well in denoising images. Compared with most denoising algorithms, the proposed algorithm is of high efficiency.

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References

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Acknowledgements

The research is supported by the NSF of China under granted nos. 61873117, 61873145, 61602229. Shandong educational science planning “special research subject for educational admission examination”, No.: ZK1337123A002. Key Research and Development Program of Shandong Province (No. 2019GGX101025).

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Authors and Affiliations

  1. School of Information Science and Engineering, Qufu Normal University, Rizhao, 276826, China

    Guoyu Yang & Yilei Wang

  2. School of Information and Electrical Engineering, Ludong University, Yantai, 264025, China

    Guoyu Yang & Banghai Xu

  3. School of Computer Science and Technology, Shandong Technology and Business University, Yantai, 264005, China

    Xiaofeng Zhang

Authors
  1. Guoyu Yang
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  2. Yilei Wang
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  3. Banghai Xu
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  4. Xiaofeng Zhang
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Corresponding author

Correspondence to Xiaofeng Zhang .

Editor information

Editors and Affiliations

  1. Rutgers University, Newark, NJ, USA

    Jaideep Vaidya

  2. Beihang University, Beijing, China

    Xiao Zhang

  3. Guangzhou University, Guangzhou, China

    Jin Li

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Yang, G., Wang, Y., Xu, B., Zhang, X. (2019). An Image Denoising Algorithm Based on Singular Value Decomposition and Non-local Self-similarity. In: Vaidya, J., Zhang, X., Li, J. (eds) Cyberspace Safety and Security. CSS 2019. Lecture Notes in Computer Science(), vol 11983. Springer, Cham. https://doi.org/10.1007/978-3-030-37352-8_44

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  • DOI: https://doi.org/10.1007/978-3-030-37352-8_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37351-1

  • Online ISBN: 978-3-030-37352-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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