• DocumentCode
    786394
  • Title

    Simultaneous iterative image restoration and evaluation of the regularization parameter

  • Author

    Kang, M.G. ; Katsaggelos, A.K.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Northwestern Unv., Evanston, IL, USA
  • Volume
    40
  • Issue
    9
  • fYear
    1992
  • fDate
    9/1/1992 12:00:00 AM
  • Firstpage
    2329
  • Lastpage
    2334
  • Abstract
    A nonlinear regularized iterative image restoration algorithm is proposed, according to which only the noise variance is assumed to be known in advance. The algorithm results from a set theoretic regularization approach, where a bound of the stabilizing functional, and therefore the regularization parameter, are updated at each iteration step. Sufficient conditions for the convergence of the algorithm are derived and experimental results are shown
  • Keywords
    convergence of numerical methods; iterative methods; picture processing; random noise; additive white Gaussian noise; algorithm convergence; experimental results; noise variance; nonlinear regularized iterative image restoration algorithm; parameter evaluation; regularization parameter; stabilising functional bound; theoretic regularization approach; Bars; Hardware; Image restoration; Interpolation; Music; Performance evaluation; Psychology; Speech coding; Testing; Timbre;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.157234
  • Filename
    157234