Wavelet-based multi-channel image denoising using fuzzy logic

Authors:
Jamal Saeedi;Ali Abedi
Affiliations:
Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran;Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran
Venue:
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Year:
2010

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Abstract

In this paper, we propose a new wavelet shrinkage algorithm based on fuzzy logic for multi-channel image denoising. In particular, intra-scale dependency within wavelet coefficients is modeled using a fuzzy feature. This feature space distinguishes between important coefficients, which belong to image discontinuity and noisy coefficients. Besides this fuzzy feature, we use inter-relation between different channels for improving the denoising performance compared to denoising each channel, separately. Then, we use the Takagi-Sugeno model based on two fuzzy features for shrinking wavelet coefficients. We examine our multi-channel image denoising algorithm in the dual-tree discrete wavelet transform domain, which is the new shiftable and modified version of discrete wavelet transform. Extensive comparisons with the state-of-the-art image denoising algorithms indicate that our image denoising algorithm has a better performance in noise suppression and edge preservation.