Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)

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The principle curvature-driven diffusion model for image de-noising

Authors
Xin Qiao
Corresponding Author
Xin Qiao
Available Online November 2013.
DOI
10.2991/icmt-13.2013.184How to use a DOI?
Keywords
Image de-noising Perona and Malik equation Principle curvature Gauss curvature Diffusion coefficient
Abstract

In this paper, we discuss a weighted average of the maximum and minimal principle curvature as the diffusion coefficient for de-noising digital images with an additive noise. The main advantage of this approach is that it preserves important structures similar to Gauss curvature-driven diffusion, and it has a stable and fast numerical algorithm. Moreover, the proposed model helps gaining better de-noising results than Gauss curvature-driven diffusion.

Copyright
© 2013, 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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<Previous Article In Volume
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Volume Title
Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
Series
Advances in Intelligent Systems Research
Publication Date
November 2013
ISBN
10.2991/icmt-13.2013.184
ISSN
1951-6851
DOI
10.2991/icmt-13.2013.184How to use a DOI?
Copyright
© 2013, 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

risenwbib
TY  - CONF
AU  - Xin Qiao
PY  - 2013/11
DA  - 2013/11
TI  - The principle curvature-driven diffusion model for image de-noising
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 1498
EP  - 1505
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.184
DO  - 10.2991/icmt-13.2013.184
ID  - Qiao2013/11
ER  -