Variational optimization based single image dehazing |
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| Affiliation: | 1. College of Information Engineering, Shenzhen University, Shenzhen, China;2. College of Mathematics and Statistics, Chongqing University, Chongqing, 401331, China;3. Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, 19716, USA;1. College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China;2. School of information science and engineering, East China University of Science & Technology, Shanghai, China;3. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, 330032, China;4. Dept. of Electronic and Information Engineering, Xi''an Jiaotong University, Xi''an 710049, China;5. School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China |
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| Abstract: | In this paper, we present a new approach for single image dehazing based on the proposed variational optimization. A hazy image captures the information about haze in terms of the transmission map and object details present in it. We propose to estimate the initial transmission map by performing the structure-aware smoothing of the hazy image. Further, we formulated a variational optimization for the estimation of final transmission, which refines the initial transmission of a hazy image. Atmospheric light can be considered to be constant throughout the scene for practical purposes. The uniform atmospheric light is computed from the dark channel of a hazy image. The exhaustive experimentation shows that the performance of the proposed method is comparable or better. |
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| Keywords: | Image dehazing Transmission Atmospheric light Haze |
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