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Efficient image compression using directionlets

dc.contributor.authorVelisavljević, Vladanen_GB
dc.contributor.authorBeferull-Lozano, Baltasaren_GB
dc.contributor.authorVetterli, Martinen_GB
dc.date.accessioned2013-05-22T14:58:28Z
dc.date.available2013-05-22T14:58:28Z
dc.date.issued2007
dc.identifier.citationVelisavljevic, V., Beferull-Lozano, B. and Vetterli, M. (2007) 'Efficient image compression using directionlets', 6th International Conference on Information, Communications & Signal Processing, Singapore, 10-13 December. Singapore: IEEE, pp.1-5.en_GB
dc.identifier.isbn9781424409839
dc.identifier.doi10.1109/ICICS.2007.4449603
dc.identifier.urihttp://hdl.handle.net/10547/292619
dc.description.abstractDirectionlets are built as basis functions of critically sampled perfect-reconstruction transforms with directional vanishing moments imposed along different directions. We combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional wavelet transform. We show that our new compression method outperforms the standard SFQ as well as the state-of-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.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4449603en_GB
dc.subjectdata compressionen_GB
dc.subjectimage codingen_GB
dc.subjectwavelet transformsen_GB
dc.titleEfficient image compression using 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 imposed along different directions. We combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional wavelet transform. We show that our new compression method outperforms the standard SFQ as well as the state-of-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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