2.50
Hdl Handle:
http://hdl.handle.net/10547/293061
Title:
Approximation power of directionlets
Authors:
Velisavljević, Vladan ( 0000-0001-9980-9368 ) ; Beferull-Lozano, Baltasar; Vetterli, Martin; Dragotti, Pier Luigi
Abstract:
In spite of the success of the standard wavelet transform (WT) in image processing, the efficiency of its representation is limited by the spatial isotropy of its basis functions built in only horizontal and vertical directions. One-dimensional (1-D) discontinuities in images (edges and contours), which are very important elements in visual perception, intersect too many wavelet basis functions and reduce the sparsity of the representation. To capture efficiently these anisotropic geometrical structures, a more complex multi-directional (M-DIR) and anisotropic transform is required. We present a new lattice-based perfect reconstruction and critically sampled anisotropic M-DIR WT (with the corresponding basis functions called directionlets) that retains the separable filtering and simple filter design from the standard two-dimensional (2-D) WT and imposes directional vanishing moments (DVM). Further-more, we show that this novel transform has non-linear approximation efficiency competitive to the other previously proposed over-sampled transform constructions.
Citation:
Velisavljevic, V.; Beferull-Lozano, B.; Vetterli, M. and Dragotti, P.-L. (2005) 'Approximation power of directionlets', IEEE International Conference on Image Processing (ICIP 2005, Genova, Italy, 14 September. Genova: IEEE, vol.1, pp.I-741
Publisher:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date:
2005
URI:
http://hdl.handle.net/10547/293061
DOI:
10.1109/ICIP.2005.1529857
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1529857
Type:
Conference papers, meetings and proceedings
Language:
en
ISBN:
0780391349
Appears in Collections:
Centre for Wireless Research (CWR)

Full metadata record

DC FieldValue Language
dc.contributor.authorVelisavljević, Vladanen_GB
dc.contributor.authorBeferull-Lozano, Baltasaren_GB
dc.contributor.authorVetterli, Martinen_GB
dc.contributor.authorDragotti, Pier Luigien_GB
dc.date.accessioned2013-05-30T13:01:41Z-
dc.date.available2013-05-30T13:01:41Z-
dc.date.issued2005-
dc.identifier.citationVelisavljevic, V.; Beferull-Lozano, B.; Vetterli, M. and Dragotti, P.-L. (2005) 'Approximation power of directionlets', IEEE International Conference on Image Processing (ICIP 2005, Genova, Italy, 14 September. Genova: IEEE, vol.1, pp.I-741en_GB
dc.identifier.isbn0780391349-
dc.identifier.doi10.1109/ICIP.2005.1529857-
dc.identifier.urihttp://hdl.handle.net/10547/293061-
dc.description.abstractIn spite of the success of the standard wavelet transform (WT) in image processing, the efficiency of its representation is limited by the spatial isotropy of its basis functions built in only horizontal and vertical directions. One-dimensional (1-D) discontinuities in images (edges and contours), which are very important elements in visual perception, intersect too many wavelet basis functions and reduce the sparsity of the representation. To capture efficiently these anisotropic geometrical structures, a more complex multi-directional (M-DIR) and anisotropic transform is required. We present a new lattice-based perfect reconstruction and critically sampled anisotropic M-DIR WT (with the corresponding basis functions called directionlets) that retains the separable filtering and simple filter design from the standard two-dimensional (2-D) WT and imposes directional vanishing moments (DVM). Further-more, we show that this novel transform has non-linear approximation efficiency competitive to the other previously proposed over-sampled transform constructions.en_GB
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1529857en_GB
dc.subjectfiltering theoryen_GB
dc.subjectimage reconstructionen_GB
dc.subjectimage representationen_GB
dc.subjectimage samplingen_GB
dc.subjectwavelet transformsen_GB
dc.titleApproximation power of directionletsen
dc.typeConference papers, meetings and proceedingsen
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