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dc.contributor.authorVelisavljević, Vladanen_GB
dc.contributor.authorBeferull-Lozano, Baltasaren_GB
dc.contributor.authorVetterli, Martinen_GB
dc.date.accessioned2013-05-22T14:56:47Z
dc.date.available2013-05-22T14:56:47Z
dc.date.issued2007
dc.identifier.citationVelisavljevic, V., Beferull-Lozano, B. and Vetterli, M. (2007) 'Efficient zerotree-based image compression with directionlets', 15th European Signal Processing Conference (EUSIPCO-2007), Poznan, Poland, 3-7 September. Poznan: EURASIP, pp.807-811.en_GB
dc.identifier.isbn9788392134022
dc.identifier.urihttp://hdl.handle.net/10547/292618
dc.description.abstractDirectionlets are built as basis functions of critically sampled perfect-reconstruction transforms with directional vanishing moments (DVMs) imposed along different directions. Here, we combine the directionlets with the spacefrequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT). We show that our new compression method outperforms the standard SFQ as well as the stateof-the-art image compression methods, such as SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the standard SFQ algorithm.
dc.language.isoenen
dc.publisherEURASIPen_GB
dc.relation.urlhttp://www.eurasip.org/Proceedings/Eusipco/Eusipco2007/Papers/b1l-f01.pdfen_GB
dc.relation.urlhttp://www.eurasip.org/Proceedings/Eusipco/Eusipco2007/start.pdfen_GB
dc.subjectimage segmentationen_GB
dc.subjectwavelet transformsen_GB
dc.titleEfficient zerotree-based image compression with directionletsen
dc.typeConference papers, meetings and proceedingsen
html.description.abstractDirectionlets are built as basis functions of critically sampled perfect-reconstruction transforms with directional vanishing moments (DVMs) imposed along different directions. Here, we combine the directionlets with the spacefrequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT). We show that our new compression method outperforms the standard SFQ as well as the stateof-the-art image compression methods, such as SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the standard SFQ algorithm.


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