A New Method for Image Denoising with Nonlocal Means

DOI

10.2991/cmes-15.2015.29How to use a DOI?

Keywords

denoise, Nonlocal Means, direction grads, Coefficient of Variation.

Abstract

Denoising is an important problem in image processing, as it can influence the following processing step and decide the final visual effect. To denoise the image and preserve the details, this paper enhances the Nonlocal Means. When estimating the value of a disturbed pixel, we use the information of edges and textures as the weights of pixels involved in calculation, instead of simple Gaussian distance weights. The weights of edge and texture are obtained by direction grads and the coefficients of variation (CV). Finally, based on the results from different images, the enhanced algorithm is shown to have better performance than traditional NLM in SSIM, and has a better visual effect in subjective evaluations.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xuyao Zhang
AU  - Zhiyong Xu
PY  - 2015/04
DA  - 2015/04
TI  - A New Method for Image Denoising with Nonlocal Means
BT  - Proceedings of the 2nd International Conference on Civil, Materials and Environmental Sciences
PB  - Atlantis Press
SP  - 99
EP  - 102
SN  - 2352-5401
UR  - https://doi.org/10.2991/cmes-15.2015.29
DO  - 10.2991/cmes-15.2015.29
ID  - Zhang2015/04
ER  -