Denoising of three dimensional data cube using bivariate wavelet shrinking

Authors:
Guangyi Chen;Tien D. Bui;Adam Krzyzak
Affiliations:
Department of Mathematics and Statistics, Concordia University, Montreal, Quebec, Canada;Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada;Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada
Venue:
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Year:
2010

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Abstract

The denoising of a natural signal/image corrupted by Gaussian white noise is a classical problem in signal/image processing. However, it is still in its infancy to denoise high dimensional data. In this paper, we extended Sendur and Selesnick's bivariate wavelet thresholding from two-dimensional image denoising to three dimensional data denoising. Our study shows that bivariate wavelet thresholding is still valid for three dimensional data. Experimental results confirm its superiority.