Central European Journal of Physics

, Volume 11, Issue 10, pp 1414–1422 | Cite as

Fractional-order TV-L2 model for image denoising

  • Dali Chen
  • Shenshen Sun
  • Congrong Zhang
  • YangQuan Chen
  • Dingyu Xue
Research Article

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.

Keywords

image denoising fractional calculus total variation majorization-minimization algorithm 

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Copyright information

© Versita Warsaw and Springer-Verlag Wien 2013

Authors and Affiliations

  • Dali Chen
    • 1
  • Shenshen Sun
    • 1
  • Congrong Zhang
    • 1
  • YangQuan Chen
    • 2
  • Dingyu Xue
    • 1
  1. 1.Information Science and EngineeringNortheastern UniversityShenyangLiaoning, China
  2. 2.MESA LabUniversity of California, MercedMercedUSA

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