NDLI: Pruned non-local means

Content Provider	IET Digital Library
Author	Ghosh, Sanjay Mandal, Amit K. Chaudhury, Kunal N.
Abstract	In non-local means (NLM), each pixel is denoised by performing a weighted averaging of its neighbouring pixels, where the weights are computed using image patches. The authors demonstrate that the denoising performance of NLM can be improved by pruning the neighbouring pixels, namely, by rejecting neighbouring pixels whose weights are below a certain threshold λ . While pruning can potentially reduce pixel averaging in uniform-intensity regions, they demonstrate that there is generally an overall improvement in the denoising performance. In particular, the improvement comes from pixels situated close to edges and corners. The success of the proposed method strongly depends on the choice of the global threshold λ , which in turn depends on the noise level and the image characteristics. They show how Stein's unbiased estimator of the mean-squared error can be used to optimally tune λ , at a marginal computational overhead. They present some representative denoising results to demonstrate the superior performance of the proposed method over NLM and its variants.
Starting Page	317
Ending Page	323
Page Count	7
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 5, Apr (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0331
Journal	IET Image Processing
Publisher Date	2017-01-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Denoising Performance Improvement Global Threshold Image Characteristic Image Denoising Image Patches Interpolation And Function Approximation Mean Square Error Method Numerical Analysis Optical, Image And Video Signal Processing Pixel Averaging Reduction Pixel Denoising Pruned NLM Pruned Nonlocal Means Stein Unbiased Estimator Uniform-intensity Region Weighted Averaging
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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