Denoising by anisotropic diffusion of independent component coefficients

Authors:
Yinghong Luo;Caixia Tao;Xiaohu Qiang;Xiangyan Zeng
Affiliations:
School of Information and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China;School of Information and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China;School of Information and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China;Department of Biological Sciences, University of California Davis, CA
Venue:
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Year:
2006

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Abstract

In this paper, we propose an image denoising method that incorporates anisotropic diffusion and independent component analysis (ICA) techniques. An image is decomposed into independent component coefficients, and anisotropic diffusion is applied to filtering the IC coefficients. The proposed method achieved much better noise suppression with minimum edge blurring compared with other denoising methods, such as original anisotropic diffusion filter and wavelet shrinkage. The effectiveness of the proposed method is demonstrated by simulation experiments on medical image denoising.