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Fractional-order TV-L2 model for image denoising

  • Research Article
  • Published:
Central European Journal of Physics

Abstract

This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.

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Author information

Authors and Affiliations

  1. Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China

    Dali Chen, Shenshen Sun, Congrong Zhang & Dingyu Xue

  2. MESA Lab, University of California, Merced, 5200 North Lake Road, Merced, CA, 95343, USA

    YangQuan Chen

Authors
  1. Dali Chen
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  2. Shenshen Sun
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  3. Congrong Zhang
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  4. YangQuan Chen
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  5. Dingyu Xue
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Corresponding author

Correspondence to Dali Chen.

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Chen, D., Sun, S., Zhang, C. et al. Fractional-order TV-L2 model for image denoising. centr.eur.j.phys. 11, 1414–1422 (2013). https://doi.org/10.2478/s11534-013-0241-1

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  • DOI: https://doi.org/10.2478/s11534-013-0241-1

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