• DocumentCode
    2598343
  • Title

    Image blur identification by using higher order statistic techniques

  • Author

    Xu, You ; Crebbin, Greg

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia
  • Volume
    3
  • fYear
    1996
  • fDate
    16-19 Sep 1996
  • Firstpage
    77
  • Abstract
    In this paper, higher order statistic (HOS) based blur identification methods are proposed to estimate blur coefficients in image restoration, in which the image is considered as a colored process. One dimensional (1-D) based blur identification algorithms are proposed, and their extensions to two dimensional (2-D) cases are discussed. The experimental results are presented to demonstrate the performance of the proposed methods in this paper
  • Keywords
    higher order statistics; image recognition; image restoration; spectral analysis; colored process; higher order statistic techniques; image blur identification; image restoration; one dimensional cases; performance; two dimensional cases; Autoregressive processes; Data mining; Degradation; Frequency domain analysis; Gaussian distribution; Higher order statistics; Image restoration; Maximum likelihood estimation; Probability density function; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1996. Proceedings., International Conference on
  • Conference_Location
    Lausanne
  • Print_ISBN
    0-7803-3259-8
  • Type

    conf

  • DOI
    10.1109/ICIP.1996.560373
  • Filename
    560373