Efficient image dehazing algorithm using multiple priors constraints

Huang Zilong; Jing Hongyuan; Chen AidongHong ChenShang Xinna

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Efficient image dehazing algorithm using multiple priors constraints

机译：Efficient image dehazing algorithm using multiple priors constraints

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摘要

In this study, a robust and efficient image dehazing technique based on the atmospheric scattering model is proposed, which effectively overcomes the limitations of a single prior condition. It is composed of a transmission estimation module and an atmospheric light estimation module. The transmission estimation module integrates multiple dehazing prior strategies and effectively optimises transmission estimation and application range. The atmospheric light estimation module uses the fuzzy C-means clustering algorithm (FCM) to estimate the atmospheric light of different scenes in an image. Unlike in the previous work, the atmospheric light in this module is a nonglobal value, and a pixel-level atmospheric light value matrix is obtained. Numerous experiments show that the proposed dehazing algorithm is superior to state-of-the-art methods.

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来源
《Journal of visual communication & image representation》 |2023年第2期|103694.1-103694.11|共11页
作者
Huang Zilong; Jing Hongyuan; Chen AidongHong ChenShang Xinna;
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作者单位

Beijing Union Univ||Coll Robot;

Beijing Union Univ||Coll Robot||Beijing Union Univ;

Beijing Union Univ||Beijing Union UnivBeijing Union Univ;

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原文格式 PDF
正文语种英语
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关键词
Image dehazing; Atmospheric scattering model; Atmospheric light estimation; Multiple prior constraints;

Efficient image dehazing algorithm using multiple priors constraints

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