MULTIPLE INPUT ADAPTIVE ITERATIVE IMAGE RESTORATION ALGORITHMS.

Aggelos K. Katsaggelos*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

Image-restoration applications where multiple distorted versions of the same original image are available are considered. A general adaptive iterative restoration algorithm is derived based on regularization techniques. The adaptivity of the algorithm is introduced in two ways: a) by a constraint operator which incorporates properties of the response of the human visual system into the restoration process, and b) by a weight matrix which assigns greater importance for the deconvolution process to areas of high spatial activity than to areas of low spatial activity. Different degrees of trust are assigned to the various distorted images, depending on the amount of noise on each image. The proposed algorithms are general and can be used for any type of linear distortion and constraint operators. It can also be used to restore signals other than images.

Original languageEnglish (US)
Pages (from-to)1179-1182
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - Jan 1 1987

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'MULTIPLE INPUT ADAPTIVE ITERATIVE IMAGE RESTORATION ALGORITHMS.'. Together they form a unique fingerprint.

Cite this