Iterative evaluation of the regularization parameter in regularized image restoration

Aggelos K Katsaggelos*, M. G. Kang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

In this paper a nonlinear regularized iterative image restoration algorithm is proposed, according to which no prior knowledge about the noise variance is assumed. The algorithm results from a set-theoretic regularization approach, where bounds of the stabilizing functional and the noise variance, which determine the regularization parameter, are updated at each iteration step. Sufficient conditions for the convergence of the algorithm, as well as an optimality criterion for the regularization parameter, are derived and experimental results are shown.

Original languageEnglish (US)
Pages (from-to)446-455
Number of pages10
JournalJournal of Visual Communication and Image Representation
Volume3
Issue number4
DOIs
StatePublished - Jan 1 1992

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

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