Paper
29 January 2007 The edge driven oriented wavelet transform: an anisotropic multidirectional representation with oriented lifting scheme
Author Affiliations +
Proceedings Volume 6508, Visual Communications and Image Processing 2007; 65080X (2007) https://doi.org/10.1117/12.704426
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
Abstract
In spite of its success, the standard 2-D discrete wavelet transform (2D-DWT) is not completely adapted to represent image entities like edges or oriented textures. Indeed the DWT is limited by the spatial isotropy of its basis functions that can not take advantage of edges regularity and moreover, direction edge that is neither vertical or horizontal is represented using many of these wavelet basis functions which does mean that DWT does not provide a sparse representation for such discontinuities. Several representations have been proposed to overcome this lack. Some of them deal with more orientations while introducing redundancy (e.g. ridgelets, curvelets, contourlets) and their implementations are not trivial or require 2-D non separable filtering. We present two oriented lifting-based schemes using separable filtering, lead by edge extraction, and inspired from bandelets and curved wavelets. An image is decomposed into a quadtree according to the edge elements orientation. For each leaf, a wavelet transform is performed along the most regular orientation, and then along its orthogonal direction. Different adapted filters may be used for these two directions in order to achieve anisotropic filtering. Our method permits also a perfect reconstruction and a critical sampling.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guillaume Jeannic, Vincent Ricordel, and Dominique Barba "The edge driven oriented wavelet transform: an anisotropic multidirectional representation with oriented lifting scheme", Proc. SPIE 6508, Visual Communications and Image Processing 2007, 65080X (29 January 2007); https://doi.org/10.1117/12.704426
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Cited by 3 scholarly publications.
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KEYWORDS
Wavelet transforms

Discrete wavelet transforms

Wavelets

Anisotropic filtering

Image segmentation

Image filtering

Chemical elements

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