Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1516
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dc.contributorDepartment of Electrical Engineering-
dc.creatorChoy, SSO-
dc.creatorChan, YH-
dc.creatorSiu, WC-
dc.date.accessioned2014-12-11T08:26:29Z-
dc.date.available2014-12-11T08:26:29Z-
dc.identifier.isbn0-7803-3192-3-
dc.identifier.urihttp://hdl.handle.net/10397/1516-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 1996 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_US
dc.rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en_US
dc.subjectAlgorithmsen_US
dc.subjectEvaluationen_US
dc.subjectImage reconstructionen_US
dc.subjectOptical variables measurementen_US
dc.subjectSignal to noise ratioen_US
dc.subjectStabilityen_US
dc.titleAn improved quantitative measure of image restoration qualityen_US
dc.typeConference Paperen_US
dcterms.abstractThe field of image restoration lacks promising comparison vehicle for judging the effectiveness of competing algorithms. By far the most widely adopted quantitative measure of image restoration quality is the SNR improvement. However, we find that the SNR improvement is of low precision, which will adversely hinder it from being a reliable measure. It is also noted that another limitation of the SNR improvement is that it cannot reveal clearly the extent to which the image quality is improved. In this paper, we devise an alternative measure for quantitative evaluation of image restoration quality. The proposed measure is much more precise than the SNR improvement. Moreover, the proposed measure contains finite and meaningful reference points in its measurements, to provide us with a better insight into the effectiveness of restoration algorithms that under study.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationThe 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing : conference proceedings : May 7-10, 1996, Atlanta, Georgia, USA, v. 3, p. 1613-1616-
dcterms.issued1996-
dc.identifier.isiWOS:A1996BG26G00407-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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