Separable bilateral nonlocal means

Nonlocal means filtering is an edge-preserving denoising method whose filter weights are determined by Gaussian weighted patch similarities. The nonlocal means filter shows superior performance in removing additive Gaussian noise at the expense of high computational complexity. In this paper, we pro...

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Bibliographic Details
Main Authors: Yong Sun Kim, Hwasup Lim, Ouk Choi, Keechang Lee, Kim, J. D. K., Changyeong Kim
Format: Conference Proceeding
Language:English
Subjects:
bilateral kernel
Complexity theory
Denoising
Gaussian noise
Image edge detection
Kernel
Noise reduction
nonlocal means
PSNR
separable filter
Online Access:Request full text
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Summary:Nonlocal means filtering is an edge-preserving denoising method whose filter weights are determined by Gaussian weighted patch similarities. The nonlocal means filter shows superior performance in removing additive Gaussian noise at the expense of high computational complexity. In this paper, we propose an efficient and effective denoising method by introducing a separable implementation of the nonlocal means filter and adopting a bilateral kernel for computing patch similarities. Experimental results demonstrate that the proposed method provides comparable performance to the original nonlocal means, with lower computational complexity.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2011.6115732