A multiple input image restoration approach

Aggelos K. Katsaggelos*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


In this paper image restoration applications, where multiple distorted versions of the same original image are available, are considered. A general adaptive restoration algorithm is derived on the basis of a set theoretic regularization technique. 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 amounts of noise. The proposed algorithm is 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. Experimental results obtained by an iterative implementation of the proposed algorithms are presented.

Original languageEnglish (US)
Pages (from-to)93-103
Number of pages11
JournalJournal of Visual Communication and Image Representation
Issue number1
StatePublished - Sep 1990

ASJC Scopus subject areas

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


Dive into the research topics of 'A multiple input image restoration approach'. Together they form a unique fingerprint.

Cite this