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Image haze removal using a hybrid of fuzzy inference system and weighted estimation

[+] Author Affiliations
Jyun-Guo Wang, Shen-Chuan Tai

National Cheng Kung University, Institute of Computer and Communication Engineering, University Road 1, Tainan 701, Taiwan

Cheng-Jian Lin

National Chin-Yi University of Technology, Department of Computer Science and Information Engineering, Taichung City 41170, Taiwan

J. Electron. Imaging. 24(3), 033027 (Jun 23, 2015). doi:10.1117/1.JEI.24.3.033027
History: Received March 1, 2015; Accepted May 20, 2015
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Abstract.  The attenuation of the light transmitted through air can reduce image quality when taking a photograph outdoors, especially in a hazy environment. Hazy images often lack sufficient information for image recognition systems to operate effectively. In order to solve the aforementioned problems, this study proposes a hybrid method combining fuzzy theory with weighted estimation for the removal of haze from images. A transmission map is first created based on fuzzy theory. According to the transmission map, the proposed method automatically finds the possible atmospheric lights and refines the atmospheric lights by mixing these candidates. Weighted estimation is then employed to generate a refined transmission map, which removes the halo artifact from around the sharp edges. Experimental results demonstrate the superiority of the proposed method over existing methods with regard to contrast, color depth, and the elimination of halo artifacts.

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Citation

Jyun-Guo Wang ; Shen-Chuan Tai and Cheng-Jian Lin
"Image haze removal using a hybrid of fuzzy inference system and weighted estimation", J. Electron. Imaging. 24(3), 033027 (Jun 23, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.3.033027


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