Over Enhancement Inhibition in Sky Region Based on Dark Channel

DOI

10.2991/icaita-18.2018.30How to use a DOI?

Keywords

dark-channel; sky area over enhanced;single image defogging; limiting

Abstract

The dark channel de-fog algorithm has a landmark significance in the field of single image fogging removal. In the original algorithm, the sky region is prone to over enhancement. Existing improved algorithms has to take lots of time and space. In order to improve the effect of defogging and make sure the operation efficiency, this paper presents a sky region overgrowth suppression algorithm, which is based on the phenomenon of that these three channel values in sky area are approaching the maximum. First, the RGB channel in the original image is separated, then histogram equalization is got. Second, a proposed limiting algorithm is used to calculate the oversaturation gray-scale information in the sky region, and then the transmission rate is obtained based on the correction of the dark channel de-fog algorithm. Finally, the output image is generated. The validity of the algorithm in this paper is verified. The suppression algorithm and the original algorithm is evaluated by using the visible side evaluation indicators. It is shows that the ratio of supersaturated pixels has been significantly reduced with slightly affecting new visible edge ratio and balanced gradient ratio. The over enhancement suppression algorithm can effectively suppress sky over enhancement. It is proved that the suppression algorithm can effectively correct the transmittance of the sky region in fog images, and be suitable for occasions where require high speed.

Copyright

© 2018, 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  - Fang Ding
AU  - Cailiang Du
AU  - Xiaojing Song
PY  - 2018/03
DA  - 2018/03
TI  - Over Enhancement Inhibition in Sky Region Based on Dark Channel
BT  - Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)
PB  - Atlantis Press
SP  - 117
EP  - 121
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-18.2018.30
DO  - 10.2991/icaita-18.2018.30
ID  - Ding2018/03
ER  -