Wavelet-based image denoising using three scales of dependency
Wavelet-based image denoising using three scales of dependency
- Author(s): G. Chen ; W.-P. Zhu ; W. Xie
- DOI: 10.1049/iet-ipr.2010.0408
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- Author(s): G. Chen 1, 2 ; W.-P. Zhu 1 ; W. Xie 2
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View affiliations
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Affiliations:
1: Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
2: Department of Mechanical and Industrial Engineering, Concordia University, Montreal, Canada
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Affiliations:
1: Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
- Source:
Volume 6, Issue 6,
August 2012,
p.
756 – 760
DOI: 10.1049/iet-ipr.2010.0408 , Print ISSN 1751-9659, Online ISSN 1751-9667
The denoising of a natural image corrupted by the Gaussian white noise is a classical problem in image processing. A new image denoising method is proposed by using three scales of dual-tree complex wavelet coefficients. The dual-tree complex wavelet transform is well known for its approximate shift invariance and better directional selectivity, which are very important in image denoising. Experiments show that the proposed method is very competitive when compared with other existing denosing methods in the literature.
Inspec keywords: white noise; Gaussian noise; wavelet transforms; trees (mathematics); image denoising
Other keywords:
Subjects: Integral transforms; Combinatorial mathematics; Computer vision and image processing techniques; Integral transforms; Other topics in statistics; Combinatorial mathematics; Optical, image and video signal processing; Other topics in statistics
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