• DocumentCode
    3547533
  • Title

    Restoration method of missing areas in still images using GMRF model

  • Author

    Ogawa, Takahiro ; Haseyama, Miki ; Kitajima, Hideo

  • Author_Institution
    Graduate Sch. of Inf. Sci. & Technol., Hokkaido Univ., Hokkaid, Japan
  • fYear
    2005
  • fDate
    23-26 May 2005
  • Firstpage
    4931
  • Abstract
    This paper proposes a GMRF (Gaussian Markov random field)-model based restoration method of missing areas in still images. The GMRF model used in the proposed method is realized by a new assumption that reasonably holds for an image source. This model can express important image features such as edges because of the use of the new assumption. Therefore, the proposed method restores the missing areas using the modified GMRF model and can correctly reconstruct the missing edges. Consequently, the proposed method achieves more accurate restoration than those of the traditional methods on both objective and subjective measures. Extensive experimental results demonstrate the improvement of the proposed method over previous methods.
  • Keywords
    Gaussian distribution; Markov processes; image representation; image restoration; GMRF model; Gaussian Markov random field; edge representation; image feature expression; missing edge reconstruction; still image missing area restoration; Area measurement; Image reconstruction; Image restoration; Information science; Interpolation; Markov random fields; Probability density function; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on
  • Print_ISBN
    0-7803-8834-8
  • Type

    conf

  • DOI
    10.1109/ISCAS.2005.1465739
  • Filename
    1465739