• DocumentCode
    2601791
  • Title

    An edge-preserving blind image restoration using hierarchical Bayesian model

  • Author

    He, Zhenya ; Zhang, Yunnong

  • Author_Institution
    Dept. of Radio Eng., Southeast Univ., Nanjing, China
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    89
  • Abstract
    Edge-preserving blind image restoration using a hierarchical Bayesian model is proposed in this paper. The restoration problem, when the point-spread function (PSF) of the degradation system is partially known, is examined. The simultaneously autoregressive image model and the fixed-f covariance model are used under a Bayesian framework. The evidence analysis approach is then used to simultaneously estimate the parameters and the image iteratively. An edge-preserving regularization operator is utilized to carry out regularization according to the local image characteristics. Numerical experiments and conclusions are given to show the effectiveness of our method.
  • Keywords
    Bayes methods; autoregressive processes; covariance analysis; edge detection; image restoration; iterative methods; optical transfer function; parameter estimation; PSF; autoregressive image models; blur restoration problems; edge-preserving blind image restoration; edge-preserving regularization operators; evidence analysis; fixed-f covariance models; hierarchical Bayesian models; iterative parameter estimation; local image characteristics; partially known degradation system point-spread functions; Bayesian methods; Covariance matrix; Degradation; Electronic mail; Helium; Image analysis; Image restoration; Parameter estimation; Stochastic processes; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2002. APCCAS '02. 2002 Asia-Pacific Conference on
  • Print_ISBN
    0-7803-7690-0
  • Type

    conf

  • DOI
    10.1109/APCCAS.2002.1115130
  • Filename
    1115130