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Conference Paper: Two methods for least squares multi-channel image restoration

TitleTwo methods for least squares multi-channel image restoration
Authors
KeywordsMathematical Techniques--Least Squares Approximations
Issue Date1991
Citation
Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing, 1991, v. 4, p. 2509-2512 How to Cite?
AbstractThe 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.
Persistent Identifierhttp://hdl.handle.net/10722/65585
ISSN

 

DC FieldValueLanguage
dc.contributor.authorGalatsanos, Nikolas Pen_HK
dc.contributor.authorKatsaggelos, Aggelos Ken_HK
dc.contributor.authorChin, Roland Ten_HK
dc.contributor.authorHillery, Allenen_HK
dc.date.accessioned2010-08-31T07:16:19Z-
dc.date.available2010-08-31T07:16:19Z-
dc.date.issued1991en_HK
dc.identifier.citationProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing, 1991, v. 4, p. 2509-2512en_HK
dc.identifier.issn0736-7791en_HK
dc.identifier.urihttp://hdl.handle.net/10722/65585-
dc.description.abstractThe 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.en_HK
dc.languageengen_HK
dc.relation.ispartofProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processingen_HK
dc.subjectMathematical Techniques--Least Squares Approximationsen_HK
dc.titleTwo methods for least squares multi-channel image restorationen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChin, Roland T: rchin@hku.hken_HK
dc.identifier.authorityChin, Roland T=rp01300en_HK
dc.description.naturelink_to_subscribed_fulltexten_HK
dc.identifier.scopuseid_2-s2.0-0026384374en_HK
dc.identifier.volume4en_HK
dc.identifier.spage2509en_HK
dc.identifier.epage2512en_HK
dc.identifier.scopusauthoridGalatsanos, Nikolas P=35562970900en_HK
dc.identifier.scopusauthoridKatsaggelos, Aggelos K=7102711302en_HK
dc.identifier.scopusauthoridChin, Roland T=7102445426en_HK
dc.identifier.scopusauthoridHillery, Allen=7003403093en_HK

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