Simultaneous multichannel image restoration and estimation of the regularization parameters

Moon Gi Kang*, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

In this correspondence, a constrained least-squares multichannel image restoration approach is proposed, in which no prior knowledge of the noise variance at each channel or the degree of smoothness of the original image is required. The regularization functional for each channel is determined by incorporating both within-channel and cross-channel information. It is shown that the proposed smoothing functional has a global minimizer.

Original languageEnglish (US)
Pages (from-to)774-778
Number of pages5
JournalIEEE Transactions on Image Processing
Volume6
Issue number5
DOIs
StatePublished - 1997

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

Fingerprint Dive into the research topics of 'Simultaneous multichannel image restoration and estimation of the regularization parameters'. Together they form a unique fingerprint.

Cite this