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The algorithms about fast non-localmeans based image denoising

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Abstract

Image denoising is still a challenge of image processing. Buades et al. proposed a nonlocal means (NL-means) approach. This method had a remarkable denoising results at high expense of computational cost. In this paper, We compared several fast non-local means methods, and proposed a new fast algorithm. Numerical experiments showed that our algorithm considerably reduced the computational cost, and obtained visually pleasant images.

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Authors and Affiliations

  1. Department of Computational and Applied Mathematics, China University of Petroleum (East China), Qingdao, 266555, China

    Li-li Xing & Tian-tian Qiao

  2. Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Li-li Xing & Qian-shun Chang

Authors
  1. Li-li Xing
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  2. Qian-shun Chang
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  3. Tian-tian Qiao
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Corresponding author

Correspondence to Li-li Xing.

Additional information

The first author is supported by the Tianyuan Special Funds of the NSFC (Grant No. 11126085) and the Fundamental Research Funds for the Central Universities (Grant No. 11CX04060A). The third author is supported by Natural Science Foundation of China University of Petroleum (East China) (Grant No. Y080805).

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Xing, Ll., Chang, Qs. & Qiao, Tt. The algorithms about fast non-localmeans based image denoising. Acta Math. Appl. Sin. Engl. Ser. 28, 247–254 (2012). https://doi.org/10.1007/s10255-012-0139-5

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  • DOI: https://doi.org/10.1007/s10255-012-0139-5

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