Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 18, Issue 5, Pages 929-941Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2009.2013082
Keywords
Curvelets; edge detection; feature extraction; shearlets; singularities; wavelets
Funding
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [0746778] Funding Source: National Science Foundation
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It is well known that the wavelet transform provides a very effective framework for analysis of multiscale edges. In this paper, we propose a novel approach based on the shearlet transform: a multiscale directional transform with a greater ability to localize distributed discontinuities such as edges. Indeed, unlike traditional wavelets, shearlets are theoretically optimal in representing images with edges and, in particular, have the ability to fully capture directional and other geometrical features. Numerical examples demonstrate that the shearlet approach is highly effective at detecting both the location and orientation of edges, and outperforms methods based on wavelets as well as other standard methods. Furthermore, the shearlet approach is useful to design simple and effective algorithms for the detection of corners and junctions.
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