Image dehazing based on haziness analysis

Authors:
Fan Guo;Jin Tang;Zi-Xing Cai
Affiliations:
School of Information Science and Engineering, Central South University, Changsha, China 410083 and Hunan Engineering Laboratory for Advanced Control and Intelligent Automation, Changsha, China 41 ...;School of Information Science and Engineering, Central South University, Changsha, China 410083;School of Information Science and Engineering, Central South University, Changsha, China 410083
Venue:
International Journal of Automation and Computing
Year:
2014

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Abstract

We present two haze removal algorithms for single image based on haziness analysis. One algorithm regards haze as the veil layer, and the other takes haze as the transmission. The former uses the illumination component image obtained by retinex algorithm and the depth information of the original image to remove the veil layer. The latter employs guided filter to obtain the refined haze transmission and separates it from the original image. The main advantages of the proposed methods are that no user interaction is needed and the computing speed is relatively fast. A comparative study and quantitative evaluation with some main existing algorithms demonstrate that similar even better quality results can be obtained by the proposed methods. On the top of haze removal, several applications of the haze transmission including image refocusing, haze simulation, relighting and 2-dimensional (2D) to 3-dimensional (3D) stereoscopic conversion are also implemented.