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Article: Iterative Wiener filters for image restoration

TitleIterative Wiener filters for image restoration
Authors
KeywordsMathematical Techniques - Convergence of Numerical Methods
Signal Filtering and Prediction
Issue Date1991
PublisherIEEE
Citation
Ieee Transactions On Signal Processing, 1991, v. 39 n. 8, p. 1892-1899 How to Cite?
AbstractThe iterative Wiener filter, which successively uses the Wiener-filtered signal as an improved prototype to update the covariance estimates, is investigated. The convergence properties of this iterative filter are analyzed. It has been shown that this iterative process converges to a signal which does not correspond to the minimum mean-squared-error solution. Based on the analysis, an alternate iterative filter is proposed to correct for the convergence error. The theoretical performance of the filter has been shown to give minimum mean-squared error. In practical implementation when there is unavoidable error in the covariance computation, the filter may still result in undesirable restoration. Its performance has been investigated and a number of experiments in a practical setting were conducted to demonstrate its effectiveness.
Persistent Identifierhttp://hdl.handle.net/10722/65537
ISSN
2015 Impact Factor: 2.624
2015 SCImago Journal Rankings: 2.004
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHillery, Allen Den_HK
dc.contributor.authorChin, Roland Ten_HK
dc.date.accessioned2010-08-31T07:15:12Z-
dc.date.available2010-08-31T07:15:12Z-
dc.date.issued1991en_HK
dc.identifier.citationIeee Transactions On Signal Processing, 1991, v. 39 n. 8, p. 1892-1899en_HK
dc.identifier.issn1053-587Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/65537-
dc.description.abstractThe iterative Wiener filter, which successively uses the Wiener-filtered signal as an improved prototype to update the covariance estimates, is investigated. The convergence properties of this iterative filter are analyzed. It has been shown that this iterative process converges to a signal which does not correspond to the minimum mean-squared-error solution. Based on the analysis, an alternate iterative filter is proposed to correct for the convergence error. The theoretical performance of the filter has been shown to give minimum mean-squared error. In practical implementation when there is unavoidable error in the covariance computation, the filter may still result in undesirable restoration. Its performance has been investigated and a number of experiments in a practical setting were conducted to demonstrate its effectiveness.en_HK
dc.languageengen_HK
dc.publisherIEEEen_HK
dc.relation.ispartofIEEE Transactions on Signal Processingen_HK
dc.subjectMathematical Techniques - Convergence of Numerical Methodsen_HK
dc.subjectSignal Filtering and Predictionen_HK
dc.titleIterative Wiener filters for image restorationen_HK
dc.typeArticleen_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.doi10.1109/78.91161en_HK
dc.identifier.scopuseid_2-s2.0-0026203860en_HK
dc.identifier.volume39en_HK
dc.identifier.issue8en_HK
dc.identifier.spage1892en_HK
dc.identifier.epage1899en_HK
dc.identifier.isiWOS:A1991FY32500019-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridHillery, Allen D=7003403093en_HK
dc.identifier.scopusauthoridChin, Roland T=7102445426en_HK

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