19 July 2013 A gradient-based adaptive nonlocal means algorithm for image denoising
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Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 887807 (2013) https://doi.org/10.1117/12.2030639
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China
Abstract
In this paper, a modified adaptive nonlocal means (ANLM) filter is investigated for image denoising by introducing the image gradient into the classical nonlocal means filter. The proposed algorithm takes the orientation of matching neighborhood into consideration and can adaptively select the filtering parameter based on image gradient. Moreover, the symmetry or approximate symmetry of some filtered images is also considered. Therefore, comparing with the classical nonlocal means filter, the new method can exploit much more similar pixels. The proposed approach is applied to several real images corrupted by white Gaussian noise with different standard deviation. The comparative experimental results show that the improved ANLM filter obtains superior denoising performance.
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Quan Zhang, Quan Zhang, Limin Luo, Limin Luo, Zhiguo Gui, Zhiguo Gui, Yuanjin Li, Yuanjin Li, } "A gradient-based adaptive nonlocal means algorithm for image denoising", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 887807 (19 July 2013); doi: 10.1117/12.2030639; https://doi.org/10.1117/12.2030639
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