Wavelet-based image compression by hierarchical quantization indexing

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dc.authorid0000-0002-6842-1528
dc.contributor.authorAteş, Hasan Fehmien_US
dc.contributor.authorTamer, Enginen_US
dc.date.accessioned2019-08-31T12:10:23Z
dc.date.accessioned2019-08-05T16:05:00Z
dc.date.available2019-08-31T12:10:23Z
dc.date.available2019-08-05T16:05:00Z
dc.date.issued2009
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractIn this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Despite its simplicity, the algorithm produces PSNR results that are competitive with the state-of-art coders in literature.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationAteş, H. F. & Tamer, E. (2009). Wavelet-based image compression by hierarchical quantization indexing. Paper presented at the 2117-2121.en_US
dc.identifier.endpage2121
dc.identifier.issn2219-5491
dc.identifier.scopus2-s2.0-84863732181
dc.identifier.scopusqualityN/A
dc.identifier.startpage2117
dc.identifier.urihttps://hdl.handle.net/11729/1975
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAteş, Hasan Fehmien_US
dc.institutionauthorTamer, Enginen_US
dc.institutionauthorid0000-0002-6842-1528
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relation.ispartofEuropean Signal Processing Conferenceen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectIndexesen_US
dc.subjectEncodingen_US
dc.subjectPSNRen_US
dc.subjectAbstractsen_US
dc.subjectBit rateen_US
dc.subjectComplexity theoryen_US
dc.subjectData compressionen_US
dc.subjectImage classificationen_US
dc.subjectImage codingen_US
dc.subjectIndexingen_US
dc.subjectWavelet transformsen_US
dc.subjectWavelet-based image compressionen_US
dc.subjectHierarchical quantization indexingen_US
dc.subjectEfficient codingen_US
dc.subjectQuantized wavelet coefficientsen_US
dc.subjectHierarchical classification mapen_US
dc.subjectRate-distortion cost analysisen_US
dc.subjectClass assignmentsen_US
dc.subjectCost analysisen_US
dc.subjectHierarchical classificationen_US
dc.subjectMembership informationen_US
dc.subjectQuantization indexen_US
dc.subjectRate distortionsen_US
dc.subjectWavelet coefficientsen_US
dc.subjectWavelet subbandsen_US
dc.subjectCost accountingen_US
dc.subjectImage compressionen_US
dc.subjectOptimizationen_US
dc.subjectSignal processingen_US
dc.subjectForestryen_US
dc.titleWavelet-based image compression by hierarchical quantization indexingen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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