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Article: ERROR ANALYSIS OF A CLASS OF CONSTRAINED ITERATIVE RESTORATION ALGORITHMS.

TitleERROR ANALYSIS OF A CLASS OF CONSTRAINED ITERATIVE RESTORATION ALGORITHMS.
Authors
KeywordsMATHEMATICAL TECHNIQUES - Error Analysis
Issue Date1985
Citation
Ieee Transactions On Acoustics, Speech, And Signal Processing, 1985, v. ASSP-33 n. 6, p. 1593-1598 How to Cite?
AbstractThe problem of noise stability in a class of iterative image restoration algorithms is investigated. The algorithm is a Gerchberg-Papoulis type algorithm that utilizes incomplete information and partial constraints to specify constraint operators for the iteration. The iteration, in the absence of noise, converges to a unique solution. In the presence of noise, the restoration is considered as an ill-posed problem and noise stability of the algorithm is investigated. A general error-analysis method is derived to predict the optimal number of iterations that minimizes the mean-square error between the ideal and the reconstructed image. An investigation of the tradeoff between signal reconstruction and noise amplification shows that by using prior knowledge of the signal and noise statistics, it is possible to achieve optimal restoration. Simulations verify the theoretical results.
Persistent Identifierhttp://hdl.handle.net/10722/65534
ISSN

 

DC FieldValueLanguage
dc.contributor.authorYeh, ChiaLungen_HK
dc.contributor.authorChin, Roland Ten_HK
dc.date.accessioned2010-08-31T07:15:10Z-
dc.date.available2010-08-31T07:15:10Z-
dc.date.issued1985en_HK
dc.identifier.citationIeee Transactions On Acoustics, Speech, And Signal Processing, 1985, v. ASSP-33 n. 6, p. 1593-1598en_HK
dc.identifier.issn0096-3518en_HK
dc.identifier.urihttp://hdl.handle.net/10722/65534-
dc.description.abstractThe problem of noise stability in a class of iterative image restoration algorithms is investigated. The algorithm is a Gerchberg-Papoulis type algorithm that utilizes incomplete information and partial constraints to specify constraint operators for the iteration. The iteration, in the absence of noise, converges to a unique solution. In the presence of noise, the restoration is considered as an ill-posed problem and noise stability of the algorithm is investigated. A general error-analysis method is derived to predict the optimal number of iterations that minimizes the mean-square error between the ideal and the reconstructed image. An investigation of the tradeoff between signal reconstruction and noise amplification shows that by using prior knowledge of the signal and noise statistics, it is possible to achieve optimal restoration. Simulations verify the theoretical results.en_HK
dc.languageengen_HK
dc.relation.ispartofIEEE Transactions on Acoustics, Speech, and Signal Processingen_HK
dc.subjectMATHEMATICAL TECHNIQUES - Error Analysisen_HK
dc.titleERROR ANALYSIS OF A CLASS OF CONSTRAINED ITERATIVE RESTORATION ALGORITHMS.en_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.scopuseid_2-s2.0-0022205588en_HK
dc.identifier.volumeASSP-33en_HK
dc.identifier.issue6en_HK
dc.identifier.spage1593en_HK
dc.identifier.epage1598en_HK
dc.identifier.scopusauthoridYeh, ChiaLung=7401671792en_HK
dc.identifier.scopusauthoridChin, Roland T=7102445426en_HK

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