Multimedia Tools and Applications

, Volume 78, Issue 23, pp 33401–33414 | Cite as

Estimation of atmospheric light based on gaussian distribution

  • Wenbo Zhang
  • Jinbo Lu
  • Xiaobo Xu
  • Xiaorong HouEmail author


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.


Image defog Estimation of atmospheric light Statistical clustering Gaussian distribution Image quality evaluation 



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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Automation EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.China Electronics Technology Cyber Security Co., Ltd.ChengduChina

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