Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

A Denoising Algorithm for Complex Surface Image based on Adaptive Gaussian Filter Model

Authors
Lizhong Tu, Jiande Zhang, Qing Yang, Yan Zhuang
Corresponding Author
Lizhong Tu
Available Online May 2017.
DOI
10.2991/icmeit-17.2017.39How to use a DOI?
Keywords
Gaussian Filter, Adaptive filter, Image denoising, Complex surface.
Abstract

This paper presents an adaptive Gaussian filter model to solve complex curve surface image denosing problem. Based on the considering of local distribution characteristics of image noise, an adaptive Gaussian filter model is constructed by introduced an automatic adjusting smooth scale parameter, which is calculated by the distance of the gray value of the current pixel and the average gray value of all pixel in the window. Experimental results show that the adaptive denosing strategy is able to remove noise and preserve details of complex curve surface. The researched model is superior to conventional Gaussian filter model.

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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Volume Title
Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
Series
Advances in Computer Science Research
Publication Date
May 2017
ISBN
978-94-6252-338-8
ISSN
2352-538X
DOI
10.2991/icmeit-17.2017.39How to use a DOI?
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/).

Cite this article

TY  - CONF
AU  - Lizhong Tu
AU  - Jiande Zhang
AU  - Qing Yang
AU  - Yan Zhuang
PY  - 2017/05
DA  - 2017/05
TI  - A Denoising Algorithm for Complex Surface Image based on Adaptive Gaussian Filter Model
BT  - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
PB  - Atlantis Press
SP  - 216
EP  - 219
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-17.2017.39
DO  - 10.2991/icmeit-17.2017.39
ID  - Tu2017/05
ER  -