Fast Single Image Dehazing Based on Interval Estimation

LIU Haibo; YANG Jie; WU Zhengping; ZHANG Qingnian; DENG Yong

doi:10.11999/JEIT150403

Volume 38 Issue 2

Feb. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(2): 381-388

LIU Haibo, YANG Jie, WU Zhengping, ZHANG Qingnian, DENG Yong. Fast Single Image Dehazing Based on Interval Estimation[J]. Journal of Electronics & Information Technology, 2016, 38(2): 381-388. doi: 10.11999/JEIT150403

Citation:

LIU Haibo, YANG Jie, WU Zhengping, ZHANG Qingnian, DENG Yong. Fast Single Image Dehazing Based on Interval Estimation[J]. Journal of Electronics & Information Technology, 2016, 38(2): 381-388. doi: 10.11999/JEIT150403

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Fast Single Image Dehazing Based on Interval Estimation

doi: 10.11999/JEIT150403

1.
2.
(Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China)

Funds:

The National Natural Science Foundation of China (51479159), Soft Science Project of Chinas Ministry of Transport (2013-322-811-470)

Received Date: 2015-04-08
Rev Recd Date: 2015-10-26
Publish Date: 2016-02-19

Abstract

Abstract

In order to solve the problem of degraded images captured in hazy weather, a single image dehazing method based on interval estimation is proposed. From the atmospheric scattering model, the minimal filtering and gray-scale opening operation are used to estimate the value of atmospheric light based on dark channel prior theory. At the same time, the initial estimated value of medium transmission is defined. Then, the white balance is performed and the atmospheric scattering model is simplified. Secondly, the simplified atmospheric scattering model and initial estimated value of medium transmission are used to estimate the dark channel value of scene albedo, which is adopted to obtain the coarse estimated value of medium transmission. The final estimated value of medium transmission is obtained by getting through image fusion, joint bilateral filtering and range adjustment. Finally, the simplified atmospheric scattering model and tone mapping are adopted to get the restored image. Experimental results show that the proposed algorithm has a high computation speed, effectively improves the clarity and contrast of restored image, and obtains good color fidelity.
- Image dehazing,
- Interval estimation,
- Dark channel prior,
- Image fusion,
- Bilateral filtering

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References(35)

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