Image dehazing algorithm based on atmosphere scatters approximation model

Authors:
Zhongyi Hu;Qing Liu;Shenghui Zhou;Mingjing Huang;Fei Teng
Affiliations:
Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan, Hubei, P.R. China,Intelligent Information Systems Institute, Wenzhou University, Wenzhou, Zhejiang, P.R. China;Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan, Hubei, P.R. China,School of Automation, Wuhan University of Technology, Wuhan, Hubei, P.R. China;School of Automation, Wuhan University of Technology, Wuhan, Hubei, P.R. China;School of Automation, Wuhan University of Technology, Wuhan, Hubei, P.R. China;School of Automation, Wuhan University of Technology, Wuhan, Hubei, P.R. China
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Year:
2012

Citing 4
Cited 0

Blind Haze Separation

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Single image dehazing

ACM SIGGRAPH 2008 papers
A fast semi-inverse approach to detect and remove the haze from a single image

ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Single Image Haze Removal Using Dark Channel Prior

IEEE Transactions on Pattern Analysis and Machine Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Due to the scattered light of suspended particles in the atmosphere, the images taken in the foggy day become gray and are lack of visibility. In order to unveil the clear images structures and colors, the author propose an algorithm based on atmosphere scatters approximation model, which adopts the extended Jones Matrix and Stokes Law to calculate approximate the transmission of light in the atmosphere, so as to eliminate some of the scattered light. Both the light intensity in the atmosphere and haze concentration are obtained by means of Dark Channel Prior, afterward the extinction function for light transmission is used for calculation to restore the foggy images. The experimental results show that the algorithm can not only effectively improve scenery visual effect under different condition of haze, and provide clear pictures for machine vision applications in the foggy day.