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An airlight estimation method for image dehazing based on gray projection

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Abstract

As the key parameter of dehazing algorithms, airlight value directly affect the calculation accuracy of sky region, and any deviation will lead to the chromatic aberration in the image restoration. Many methods are proposed to address this problem, but the large amount of calculation or large deviations make them difficult to apply to real-time systems. In this paper, a fast algorithm is proposed based on the statistics of sky area’s distribution in hazy images. Firstly, fast mean filter is used to process gray image; and then the anti-interference ability of regional projection is analysied. Through the horizontal projection and vertical projection, the main sky area is quickly located, and finally the sky region are calculated by selecting some special pixels as atmospheric light. A large number of experiments show that the proposed algorithm can obtain the airlight value quickly for the images with sky region, and can be used in real-time conditions.

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Funding

This work was supported by Science and Technology Plan for Youth Innovation of Shandong’s Universities (No. 2019KJN012), Natural Science Foundation of Shandong Province (No. ZR2019FM059), National Natural Science Foundation of China (No. 61403283).

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Authors and Affiliations

  1. College of Information and Control Engineering, Weifang University, Weifang, China

    Wencheng Wang, Xiaojin Wu & Yihua Dong

  2. Department of Computer Science and Engineering, University of North Texas, Denton, TX, USA

    Xiaohui Yuan

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  1. Wencheng Wang
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  2. Xiaohui Yuan
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  4. Yihua Dong
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Contributions

WW wrote the initial manuscript and developed the main system. XY co-wrote the manuscript, XW helped design the algorithm and YD is the principal investigator of the project and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Wencheng Wang.

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Wang, W., Yuan, X., Wu, X. et al. An airlight estimation method for image dehazing based on gray projection. Multimed Tools Appl 79, 27185–27203 (2020). https://doi.org/10.1007/s11042-020-09380-w

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