• DocumentCode
    456743
  • Title

    A New Hybrid PDE Denoising Model Based on Markov Random Field

  • Author

    Wu, Ji-ying ; Ruan, Qiu-Qi

  • Author_Institution
    Inst. of Inf. Sci., Beijing Jiaotong Univ.
  • Volume
    2
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 1 2006
  • Firstpage
    338
  • Lastpage
    341
  • Abstract
    Partial differential equation (PDE) and Markov random field are two kinds of texture preserving regularized image denoising models. In this paper, the equivalence of them is proved: PDE can be derived to have the form of Markov model. Total variation (TV) is a kind of PDE, the adjacent domain of it is first order. Based on Markov theory, the adjacent domain of TV is enlarged to second order and it can contain more image information; image processed by the new TV-Markov model has little staircasing. In the new model, different coefficient function has different edge preserving property, so the new model is hybrid Using hybrid functions, the new TV-Markov model has better denoising effect, and it can preserve edge well
  • Keywords
    Markov processes; image denoising; image texture; partial differential equations; Markov random field; hybrid PDE denoising model; image texture; partial differential equation; total variation model; Biomedical imaging; Differential equations; Image denoising; Information science; Markov random fields; Noise reduction; Partial differential equations; Pixel; Radar imaging; TV;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7695-2616-0
  • Type

    conf

  • DOI
    10.1109/ICICIC.2006.211
  • Filename
    1691995