Optimal wavelet filter banks for regularized restoration of noisy images

Stephanakis, IM; Kollias, S

dc.contributor.author	Stephanakis, IM	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:15:46Z
dc.date.available	2014-03-01T01:15:46Z
dc.date.issued	2000	en
dc.identifier.issn	0278-081X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/13721
dc.subject	filter banks	en
dc.subject	wavelets	en
dc.subject	image restoration	en
dc.subject	regularization	en
dc.subject	generalized cross validation	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	GENERALIZED-CROSS-VALIDATION	en
dc.subject.other	RECONSTRUCTION	en
dc.subject.other	PARAMETER	en
dc.subject.other	DESIGN	en
dc.title	Optimal wavelet filter banks for regularized restoration of noisy images	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/BF01212465	en
heal.identifier.secondary	http://dx.doi.org/10.1007/BF01212465	en
heal.language	English	en
heal.publicationDate	2000	en
heal.abstract	Regularized image restoration methods efficiently handle the ill-posed problem of image restoration. Nevertheless, the issue of selecting the regularization parameter as well as the smoothing filter still constitutes an open research topic. A model of regularized image restoration is introduced and analyzed in this paper. The proposed model assumes that wavelet filter banks replace the smoothing filter of conventional regularized restoration. Filter factorizations for the optimal design of wavelet filter banks using the generalized-cross-validation (GCV) criterion are presented, and novel expressions of the influence matrix, which is used to calculate the GCV error, are derived. The error of the GCV method is expressed in terms of the modulation matrix of the filter bank and the modulation vector of the degradation filter. The expressions are given in general form for optimal wavelet filter bank design upon arbitrary sampling lattices. The numerical examples of image restoration using the proposed method that are presented indicate significant signal-to-noise ratio improvement, Delta(SNR), compared to image restoration methods that employ the Laplacian as the smoothing filter.	en
heal.publisher	BIRKHAUSER BOSTON INC	en
heal.journalName	CIRCUITS SYSTEMS AND SIGNAL PROCESSING	en
dc.identifier.doi	10.1007/BF01212465	en
dc.identifier.isi	ISI:000087095500002	en
dc.identifier.volume	19	en
dc.identifier.issue	2	en
dc.identifier.spage	99	en
dc.identifier.epage	119	en