Non-local means image denoising with bilateral structure tensor

DOI

10.2991/icmmita-16.2016.299How to use a DOI?

Keywords

Non-local means; bilateral structure tensor; image denoising; texture.

Abstract

Non-local means image denoising with bilateral structure tensor algorithm is put forward for the reason that Non-local means(NLM) algorithm has a weaker detail retention and noise immunity. Different from the initial structure tensor, we can get better texture description between similar blocks by using of bilateral structure tensor of noise resistance and texture features. New texture can improve the description of NLM value calculation function which filter the noise of images. Compared with traditional NLM algorithm, NLM-BST algorithm gets better image detail preservation in noise immunity. The experimental results show that operator is validated in denoising and image detail reservations.

Copyright

© 2017, 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  - Huan Li
AU  - Yi Xu
PY  - 2017/01
DA  - 2017/01
TI  - Non-local means image denoising with bilateral structure tensor
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1318
EP  - 1323
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.299
DO  - 10.2991/icmmita-16.2016.299
ID  - Li2017/01
ER  -