doi:

DOI: 10.3724/SP.J.1146.2013.00099

Journal of Electronics & Information Technology (电子与信息学报) 2013/35:12 PP.2908-2915

Non-local Means Denoising Derived from Structure-adapted Block Matching


Abstract:
A distinct non-local means denoising algorithm derived from structure-adapted block matching is proposed in this paper. Multi-scale matching of image blocks is adopted to measure similarity of local structures, which can deal with complex structural characteristics effectively and subsequently improve denoising performance. To begin with, structural region (including edges and textures) and flat region are divided by introducing Coefficient of Variation (CV) characteristics and the CV-Kmeans region classification algorithm is proposed. Furthermore, the size of similar block is adaptively selected based on average Euclidean distance between blocks in structural regions. Finally, a new non-local means algorithm is proposed to remove noise. Compared to the classical non-local means algorithm, the improved algorithm using patch probabilistic similarity and the adapted non-local means denoising algorithm, experimental results show that the proposed algorithm increases denoising performance and especially demonstrates a distinct advantage in texture images.

Key words:Image denoising,Non-local means algorithm,Adaptivity,Block matching

ReleaseDate:2014-07-21 17:04:35



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