Two methods for least squares multi-channel image restoration

Nikolas P. Galatsanos*, Aggelos K. Katsaggelos, Roland T. Chin, Allen Hillery

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The problem of multi-channel restoration using both within and between-channel deterministic information is considered. A multi-channel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images will yield suboptimal results when applied to multi-channel images, since between-channel information is not utilized. Multi-channel least squares restoration filters are developed using two approaches, the set theoretic and the constrained optimization. A geometric interpretation of the estimates of both filters is given. Color images, that is, three-channel imagery with red, green, and blue components, are considered. Constraints that capture the within and between-channel properties of color images are developed. Issues associated with the computation of the two estimates are addressed. Finally, experiments using color images are shown.

Original languageEnglish (US)
Title of host publicationProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Editors Anon
PublisherPubl by IEEE
Number of pages4
ISBN (Print)078030033
StatePublished - Dec 1 1991
EventProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91 - Toronto, Ont, Can
Duration: May 14 1991May 17 1991


OtherProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91
CityToronto, Ont, Can

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics


Dive into the research topics of 'Two methods for least squares multi-channel image restoration'. Together they form a unique fingerprint.

Cite this