Regularized iterative image restoration based on an iteratively updated convex smoothing functional

Moon Gi Kang, Aggelos K. Katsaggelos

Research output: Contribution to journalConference article

5 Citations (Scopus)

Abstract

The determination of the regularization parameter is an important issue in regularized image restoration, since it controls the trade-off between fidelity to the data and smoothness of the solution. A number of approaches have been developed in determining this parameter. In this paper, we propose the use of a regularization functional instead of a constant regularization parameter. The properties such a regularization functional should satisfy are investigated, and two specific forms of it are proposed. An iterative algorithm is proposed for obtaining a restored image. The regularization functional is defined in terms of the restored image at each iteration step, therefore allowing for the simultaneous determination of its value and the restoration of the degraded image. Both proposed iteration adaptive regularization functionals are shown to result in a smoothing functional with a global minimum, so that its iterative optimization does not depend on the initial conditions. The convergence of the algorithm is established and experimental results are shown.

Original languageEnglish
Pages (from-to)1364-1375
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2094
DOIs
Publication statusPublished - 1993 Dec 1
EventVisual Communications and Image Processing 1993 - Cambridge, MA, United States
Duration: 1993 Nov 71993 Nov 7

Fingerprint

Image Restoration
Image reconstruction
smoothing
restoration
Smoothing
Regularization
Regularization Parameter
Restoration
iteration
Iteration
Global Minimum
functionals
Fidelity
Iterative Algorithm
Smoothness
Initial conditions
Trade-offs
optimization
Optimization
Experimental Results

All Science Journal Classification (ASJC) codes

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

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Regularized iterative image restoration based on an iteratively updated convex smoothing functional. / Kang, Moon Gi; Katsaggelos, Aggelos K.

In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 2094, 01.12.1993, p. 1364-1375.

Research output: Contribution to journalConference article

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