Image Denoising Using Three Scales of Wavelet Coefficients

Authors:
Guangyi Chen;Wei-Ping Zhu
Affiliations:
Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada H3G 1M8;Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada H3G 1M8
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Year:
2008

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Abstract

The denoising of a natural image corrupted by the Gaussian white noise is a classical problem in image processing. In this paper, 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 denoising methods in the literature.