A general formulation of the weighted smoothing functional for regularized image restoration

Moon Gi Kang, A. K. Katsaggelos

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

Proposes a general form of the weighted smoothing functional for regularized image restoration. The weighting matrices which introduce the spatial adaptivity are defined as a function of the (partially) restored image. As a result no prior knowledge about the image is required but the smoothing functional to be minimized is nonlinear with respect to the unknown image. Conditions for the convexity of the functional are established. An iterative algorithm is proposed for obtaining its minimum. Sufficient conditions for the convergence of the algorithm are established. Various forms of the weighting matrices are proposed. Experimental results demonstrate the effectiveness of the approach.

Original languageEnglish
Article number413660
Pages (from-to)695-699
Number of pages5
JournalProceedings - International Conference on Image Processing, ICIP
Volume2
DOIs
Publication statusPublished - 1994 Jan 1
EventProceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA
Duration: 1994 Nov 131994 Nov 16

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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