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Conference Paper: Half-quadratic regularization, preconditioning and applications

TitleHalf-quadratic regularization, preconditioning and applications
Authors
Issue Date2001
PublisherIEEE.
Citation
International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, 2-4 May 2001, p. 32-35 How to Cite?
AbstractThe article addresses a wide class of image deconvolution or reconstruction situations where a sought image is recovered from degraded observed image. The sought solution is defined to be the minimizer of an objective function combining a data-fidelity term and an edge-preserving, convex regularization term. Our objective is to speed up the calculation of the solution in a wide range of situations. We propose a method applying pertinent preconditioning to an adapted half-quadratic equivalent form of the objective function. The optimal solution is then found using an alternating minimization (AM) scheme. We focus specifically on Huber regularization. We exhibit the possibility of getting very fast calculations while preserving the edges in the solution. Preliminary numerical results are reported to illustrate the effectiveness of our method.
Persistent Identifierhttp://hdl.handle.net/10722/46606
ISBN

 

DC FieldValueLanguage
dc.contributor.authorNg, KPen_HK
dc.date.accessioned2007-10-30T06:54:02Z-
dc.date.available2007-10-30T06:54:02Z-
dc.date.issued2001en_HK
dc.identifier.citationInternational Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, 2-4 May 2001, p. 32-35en_HK
dc.identifier.isbn962-85766-2-3en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46606-
dc.description.abstractThe article addresses a wide class of image deconvolution or reconstruction situations where a sought image is recovered from degraded observed image. The sought solution is defined to be the minimizer of an objective function combining a data-fidelity term and an edge-preserving, convex regularization term. Our objective is to speed up the calculation of the solution in a wide range of situations. We propose a method applying pertinent preconditioning to an adapted half-quadratic equivalent form of the objective function. The optimal solution is then found using an alternating minimization (AM) scheme. We focus specifically on Huber regularization. We exhibit the possibility of getting very fast calculations while preserving the edges in the solution. Preliminary numerical results are reported to illustrate the effectiveness of our method.en_HK
dc.format.extent380419 bytes-
dc.format.extent4654 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.titleHalf-quadratic regularization, preconditioning and applicationsen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=962-85766-2-3&volume=&spage=32&epage=35&date=2001&atitle=Half-quadratic+regularization,+preconditioning+and+applicationsen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ISIMP.2001.925323en_HK
dc.identifier.hkuros63243-

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