Show simple item record

dc.contributor.authorVelisavljević, Vladanen_GB
dc.contributor.authorBeferull-Lozano, Baltasaren_GB
dc.contributor.authorVetterli, Martinen_GB
dc.contributor.authorDragotti, Pier Luigien_GB
dc.date.accessioned2013-05-30T13:00:03Zen
dc.date.available2013-05-30T13:00:03Zen
dc.date.issued2006en
dc.identifier.citationVelisavljevic, V., Beferull-Lozano, B., Vetterli, M. and Dragotti, P. (2006) 'Low-rate reduced complexity image compression using directionlets', IEEE International Conference on Image ICIP-2006, Atlanta, GA, USA, 8-11 October 2006. Atlanta: IEEE, pp.1601-1604en_GB
dc.identifier.isbn1424404819en
dc.identifier.doi10.1109/ICIP.2006.312615en
dc.identifier.urihttp://hdl.handle.net/10547/293059en
dc.description.abstractThe standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) discontinuities, like edges and contours, that are anisotropic and characterized by geometrical regularity along different directions. In our previous work, we proposed a construction of critically sampled perfect reconstruction anisotropic transform with directional vanishing moments (DVM) imposed in the corresponding basis functions, called directionlets. Here, we show that the computational complexity of our transform is comparable to the complexity of the standard 2-D WT and substantially lower than the complexity of other similar approaches. We also present a zerotree-based image compression algorithm using directionlets that strongly outperforms the corresponding method based on the standard wavelets at low bit rates
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4106851en_GB
dc.subjectdata compressionen_GB
dc.subjectimage codingen_GB
dc.subjectimage reconstructionen_GB
dc.subjectwavelet transformsen_GB
dc.subjectimage segmentationen_GB
dc.titleLow-rate reduced complexity image compression using directionletsen
dc.typeConference papers, meetings and proceedingsen
html.description.abstractThe standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) discontinuities, like edges and contours, that are anisotropic and characterized by geometrical regularity along different directions. In our previous work, we proposed a construction of critically sampled perfect reconstruction anisotropic transform with directional vanishing moments (DVM) imposed in the corresponding basis functions, called directionlets. Here, we show that the computational complexity of our transform is comparable to the complexity of the standard 2-D WT and substantially lower than the complexity of other similar approaches. We also present a zerotree-based image compression algorithm using directionlets that strongly outperforms the corresponding method based on the standard wavelets at low bit rates


This item appears in the following Collection(s)

  • Centre for Wireless Research (CWR)
    The Centre for Wireless Research brings together expertise in the areas of mobile and wireless sensor networks. The breadth and depth of the expertise make the Centre rich with research and innovation potential.

Show simple item record