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Estimation of atmospheric light based on gaussian distribution

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Abstract

Existing defogging algorithms use a small number of sample points to estimate the atmospheric light, which leads to poor defogging effect. To solve this problem, a novel Gaussian distribution based algorithm for atmospheric light estimation is proposed. The algorithm has the following features: it uses a brightness threshold to select the candidate points to increase the number of initial samples; it uses clustering algorithms to merge the point clusters for increasing the samples included in the candidate point cluster; it uses a proportional threshold to filter out unreasonable point clusters; it regards each candidate point cluster as a single light source and calculates their influence on surrounding pixels with a Gaussian-distribution-based model; and it uses an atmospheric light map (instead of a constant value) to restore the image. The experimental results suggest that the defogging results produced by the proposed algorithm look more natural than the original algorithm under subjective vision and the objective image quality evaluation indicators are also excellent.

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Authors and Affiliations

  1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Wenbo Zhang, Jinbo Lu & Xiaorong Hou

  2. China Electronics Technology Cyber Security Co., Ltd., Chengdu, China

    Wenbo Zhang & Xiaobo Xu

Authors
  1. Wenbo Zhang
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  2. Jinbo Lu
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  3. Xiaobo Xu
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  4. Xiaorong Hou
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Correspondence to Xiaorong Hou.

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Zhang, W., Lu, J., Xu, X. et al. Estimation of atmospheric light based on gaussian distribution. Multimed Tools Appl 78, 33401–33414 (2019). https://doi.org/10.1007/s11042-019-7401-2

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  • DOI: https://doi.org/10.1007/s11042-019-7401-2

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