• DocumentCode
    2849697
  • Title

    Optimal determination of regularization parameters and the stabilizing operator

  • Author

    Leung, C.M. ; Lu, W.-S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
  • fYear
    1995
  • fDate
    17-19 May 1995
  • Firstpage
    403
  • Lastpage
    406
  • Abstract
    The aim of image restoration is to make an estimate of a degraded image as good as possible. The Tikhonov (1964) regularization approach has long been utilized for restoring images that are contaminated by noise and are blurred due for example to camera defocusing or linear motion. It is posed as a least-squares approximation problem in the l 2 space that provides a parameterized tradeoff between accuracy and smoothness of the restored image. Several methods of choosing the regularization parameter and the stabilizing operator are proposed via optimization approach
  • Keywords
    image restoration; least squares approximations; optimisation; stability; Tikhonov regularization approach; blurred images; camera defocusing; degraded image; image restoration; least-squares approximation problem; linear motion; noise contaminated image; optimization approach; regularization parameters; stabilizing operator; Additive white noise; Cameras; Constraint optimization; Degradation; Ear; Frequency locked loops; Image restoration; Laplace equations; Optimization methods; Pollution measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Computers, and Signal Processing, 1995. Proceedings., IEEE Pacific Rim Conference on
  • Conference_Location
    Victoria, BC
  • Print_ISBN
    0-7803-2553-2
  • Type

    conf

  • DOI
    10.1109/PACRIM.1995.519554
  • Filename
    519554