• DocumentCode
    3161636
  • Title

    Restoration of original image from deteriorated image by probabilistic image model

  • Author

    Karita, Yuji ; Tanaka, Toshiyuki

  • Author_Institution
    Dept. of Appl. Phys. & Physico-Inf., Keio Univ., Yokohama
  • fYear
    2008
  • fDate
    20-22 Aug. 2008
  • Firstpage
    3096
  • Lastpage
    3100
  • Abstract
    The conventional noise removal methods are based on spatial filtering and frequency filtering. But these methods have problems associated with degradation of image along side the noise removal. In this study, we propose the method that formulates noise based on multi-dimension Gaussian distribution and restore original image from deteriorated image by Probabilistic inference based on Bayesian statistics. The effectiveness of the proposed method has been validated using benchmark images.
  • Keywords
    Bayes methods; Gaussian distribution; image restoration; probability; Bayesian statistics; deteriorated image; image restoration; multidimension Gaussian distribution; probabilistic image model; probabilistic inference; Bayesian methods; Filtering; Frequency; Gaussian distribution; Gaussian noise; Image restoration; Statistical distributions; Statistics; Wiener filter; Working environment noise; Bayesian statistics; Gaussian white noise; image restoration; maximum likelihood estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference, 2008
  • Conference_Location
    Tokyo
  • Print_ISBN
    978-4-907764-30-2
  • Electronic_ISBN
    978-4-907764-29-6
  • Type

    conf

  • DOI
    10.1109/SICE.2008.4655196
  • Filename
    4655196