Image denoising with complex ridgelets

Authors:
G. Y. Chen;B. Kégl
Affiliations:
Department of Computer Science and Operations Research, University of Montreal, CP 6128 succ. Centre-Ville, Montreal, Quebec, Canada H3C 3J7;Department of Computer Science and Operations Research, University of Montreal, CP 6128 succ. Centre-Ville, Montreal, Quebec, Canada H3C 3J7
Venue:
Pattern Recognition
Year:
2007

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Abstract

In this paper, we propose a novel image denoising method by incorporating the dual-tree complex wavelets into the ordinary ridgelet transform. The approximate shift invariant property of the dual-tree complex wavelet and the high directional sensitivity of the ridgelet transform make the new method a very good choice for image denoising. We apply the digital complex ridgelet transform to denoise some standard images corrupted with additive white noise. Experimental results show that the new method outperforms VisuShrink, the ordinary ridgelet image denoising, and wiener2 filter both in terms of peak signal-to-noise ratio and in visual quality. In particular, our method preserves sharp edges better while removing white noise. Complex ridgelets could be applied to curvelet image denoising as well.