Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

An Image Dehazing Method Based on Atmospheric Veil

Authors
Shifeng Li, Dengyin Zhang, Mingye Ju
Corresponding Author
Shifeng Li
Available Online March 2017.
DOI
https://doi.org/10.2991/ifmca-16.2017.92How to use a DOI?
Keywords
Image dehazing, Total variation model, Atmospheric veil, Haze density feature
Abstract
At present, most of the image dehazing treatments have residual haze at depth of field and obvious over-enhancement phenomenon in bright area. To solve these problems, we propose a new method of fast image dehazing based on the atmospheric veil. Firstly, we use the total variation model to estimate the atmosphere veil, which can preserve the edge characteristics of image on the premise of improving the computational efficiency. Then, aiming at the failure of bright area of the atmosphere veil, we propose a fault-tolerant mechanism based on haze density feature to improve the universality of the algorithm. The experimental results show that our method has better visual effect than some existing mainstream dehazing techniques, and its efficiency also has obvious advantages.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
978-94-6252-307-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifmca-16.2017.92How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shifeng Li
AU  - Dengyin Zhang
AU  - Mingye Ju
PY  - 2017/03
DA  - 2017/03
TI  - An Image Dehazing Method Based on Atmospheric Veil
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 595
EP  - 600
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.92
DO  - https://doi.org/10.2991/ifmca-16.2017.92
ID  - Li2017/03
ER  -