• DocumentCode
    3094056
  • Title

    Deblurring two-tone images by a joint estimation approach using higher-order statistics

  • Author

    Li, Ta-Hsin ; Lii, Ke-Shin

  • Author_Institution
    Dept. of Stat., Texas A&M Univ., College Station, TX, USA
  • fYear
    1997
  • fDate
    21-23 Jul 1997
  • Firstpage
    108
  • Lastpage
    111
  • Abstract
    A method is proposed for the restoration of linearly blurred two-tone images without requiring the knowledge of the blur parameters. The method jointly estimates the original image and the blur parameters based on some statistical parameters at the output of an inverse filter. Unlike some other blind image restoration procedures, the proposed method does not require the estimation or modeling of the statistical properties of the original image, yet can be justified even for non-i.i.d. images
  • Keywords
    filtering theory; higher order statistics; image restoration; image segmentation; minimisation; parameter estimation; blur parameters; deblurring two-tone images; higher-order statistics; image restoration; inverse filter; joint estimation approach; statistical parameters; Blind equalizers; Character recognition; Deconvolution; Eyes; Higher order statistics; Humans; Image recognition; Image restoration; Nonlinear filters; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
  • Conference_Location
    Banff, Alta.
  • Print_ISBN
    0-8186-8005-9
  • Type

    conf

  • DOI
    10.1109/HOST.1997.613497
  • Filename
    613497