Title
Multichannel Nonlocal Means Fusion for Color Image Denoising
Abstract
In this paper, we propose an advanced color image denoising scheme called multichannel nonlocal means fusion (MNLF), where noise reduction is formulated as the minimization of a penalty function. An inherent feature of color images is the strong interchannel correlation, which is introduced into the penalty function as additional prior constraints to expect a better performance. The optimal solution of the minimization problem is derived, consisting of constructing and fusing multiple nonlocal means (NLM) spanning all three channels. The weights in the fusion are optimized to minimize the overall mean squared denoising error, with the help of the extended and adapted Stein's unbiased risk estimator (SURE). Simulations on representative test images under various noise levels verify the improvement brought by the multichannel NLM, compared to the traditional single-channel NLM. In the meantime, MNLF provides competitive performance both in terms of the color peak signal-to-noise ratio and in perceptual quality when compared with other state-of-the-art benchmarks.
Year
DOI
Venue
2013
10.1109/TCSVT.2013.2269020
IEEE Transactions on Circuits and Systems for Video Technology
Keywords
Field
DocType
color peak signal-to-noise ratio,overall mean squared denoising error,multichannel nonlocal means fusion,stein's unbiased risk estimator,optimal solution,image fusion,intercolor correlation,perceptual quality,color image denoising,strong interchannel correlation,image denoising,advanced color image denoising scheme,representative test images,noise reduction,noise levels,nonlocal means,minimization problem,minimisation,image colour analysis,penalty function
Noise reduction,Computer vision,Image fusion,Pattern recognition,Non-local means,Computer science,Minification,Minimisation (psychology),Artificial intelligence,Penalty method,Color image,Estimator
Journal
Volume
Issue
ISSN
23
11
1051-8215
Citations 
PageRank 
References 
5
0.43
38
Authors
6
Name
Order
Citations
PageRank
Jingjing Dai16710.96
Oscar C. Au21592176.54
Lu Fang334355.27
Chao Pang414319.04
Feng Zou555646.05
Jiali Li6499.29