A Novel Weighting Method Using Fuzzy Set Theory for Spatial Adaptive Patch-based Image Denoising
نویسندگان
چکیده
Based on fuzzy set theory, this paper proposes a novel weighting method for spatial adaptive patch-based image denoising algorithm which can be considered as an extension of nonlocal means filtering. First, a fuzzy clustering algorithm for weighting data points is applied to reduce the estimate bias which arises from the unrelated points. The weighting function is determined by optimal fuzzy partitions of the similarity of image patches. Then, the control parameter of the weighting function for each iterative step is modified to make a more rational weight distribution. Finally, a fuzzy control idea is introduced to deal with residual noisy pixels which fail in fuzzy clustering because of lacking similar patches in their neighborhoods. Experiment results show that the proposed weighting method improves the performance of the original algorithm and preserves more details in images.
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