Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1503
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dc.contributorDepartment of Electrical Engineering-
dc.creatorChan, YH-
dc.creatorSiu, WC-
dc.date.accessioned2014-12-11T08:26:26Z-
dc.date.available2014-12-11T08:26:26Z-
dc.identifier.isbn0-7803-4455-3-
dc.identifier.urihttp://hdl.handle.net/10397/1503-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 1998 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.subjectComputational complexityen_US
dc.subjectImage analysisen_US
dc.subjectImage qualityen_US
dc.subjectImage reconstructionen_US
dc.subjectMathematical transformationsen_US
dc.subjectOptimizationen_US
dc.subjectVector quantizationen_US
dc.titleAn efficient weight optimization algorithm for image representation using nonorthogonal basis vectorsen_US
dc.typeConference Paperen_US
dcterms.abstractThough image-coding techniques that employ subsets of nonorthogonal basis images chosen from two or more transform domains have been shown consistently to yield higher image quality than those based on one transform for a fixed compression ratio, they have not been widely employed due to their very high computational complicity of existing realization approaches. This paper presents a new realization approach for mixed-transform image representation. Computational complexity can be greatly reduced compared with existing approaches.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationISCAS '98 : proceedings of the 1998 IEEE International Symposium on Circuits and Systems : May 31-June 3, 1998, Monterey, CA, p. IV17-IV20-
dcterms.issued1998-
dc.identifier.isiWOS:000075224600445-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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