Directional wavelet transforms and frames
dc.contributor.author | Velisavljević, Vladan | en_GB |
dc.contributor.author | Dragotti, Pier Luigi | en_GB |
dc.contributor.author | Vetterli, Martin | en_GB |
dc.date.accessioned | 2013-05-31T10:30:51Z | |
dc.date.available | 2013-05-31T10:30:51Z | |
dc.date.issued | 2002 | |
dc.identifier.citation | Velisavljevic, V.; Dragotti, P. and Vetterli, M. (2002) 'Directional wavelet transforms and frames', International Conference on Image Processing, Rochester, NY, USA, 24-28 June 2002. Rochester: IEEE, vol.3, pp.589-592 | en_GB |
dc.identifier.isbn | 0780376226 | |
dc.identifier.doi | 10.1109/ICIP.2002.1039039 | |
dc.identifier.uri | http://hdl.handle.net/10547/293130 | |
dc.description.abstract | The application of the wavelet transform in image processing is most frequently based on a separable transform. Lines and columns in an image are treated independently and the basis functions are simply products of corresponding one-dimensional functions. Such a method keeps simplicity in design and computation. A new two-dimensional approach is proposed, which retains the simplicity of separable processing, but allows more directionalities. The method can be applied in many areas like denoising, nonlinear approximation and compression. The results on nonlinear approximation and denoising show interesting gains compared to the standard two-dimensional analysis. | |
dc.language.iso | en | en |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | en_GB |
dc.relation.url | http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1039039 | en_GB |
dc.subject | data compression | en_GB |
dc.subject | image coding | en_GB |
dc.subject | wavelet transforms | en_GB |
dc.title | Directional wavelet transforms and frames | en |
dc.type | Conference papers, meetings and proceedings | en |
html.description.abstract | The application of the wavelet transform in image processing is most frequently based on a separable transform. Lines and columns in an image are treated independently and the basis functions are simply products of corresponding one-dimensional functions. Such a method keeps simplicity in design and computation. A new two-dimensional approach is proposed, which retains the simplicity of separable processing, but allows more directionalities. The method can be applied in many areas like denoising, nonlinear approximation and compression. The results on nonlinear approximation and denoising show interesting gains compared to the standard two-dimensional analysis. |
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.