Blind Image Denoising Based on Noise Level Estimation
FANG Shuai1, XIA Xiu-Shan1, CAO Yang2, YU Lei1
1.School of Computer and Information, Hefei University of Technology, Hefei 230009 2.Department of Automation, University of Science and Technology of China, Hefei 230027
Abstract Block-matching and 3D filtering (BM3D) algorithm is one of the best image denoising algorithms. However, the application of the algorithm is constrained owing to high time complexity and the requirement of exact image noise level parameter. Thus, a fast block-matching and 3D filtering (FBM3D) algorithm is proposed, which uses a grid-based block-matching strategy. Then, the image noise is refined by iteration in which the starting point is set by SVM learning and the ending point is decided by image quality. The experimental results show that the proposed algorithm has a significant improvement in computation efficiency, visual effects and quantifiable performance evaluation.
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2015, Vol. 28 
