Paper
21 July 2023 A transmission line image defogging algorithm based on improved transmission estimation and color bias correction
HuiRong Zhang, Liang Fan, ChengJiu Liao, QiuMei Wang, HuaChao Chen
Author Affiliations +
Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 127172A (2023) https://doi.org/10.1117/12.2685351
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China
Abstract
UAV inspection of overhead transmission lines is a common means for power grid companies to conduct defect detection, but in bad weather, the performance of the target detection algorithm deployed on the onboard equipment often decreases significantly. Based on the classical atmospheric light scattering model, the atmospheric light estimation is first done more accurately by separating the sky area. In terms of transmission estimation, the synthetic transmission is estimated from comprehensive information loss and image texture information weighting, and finally the color bias is corrected to realize the target image fog processing. The experimental results show that the proposed algorithm can significantly improve the clarity of transmission line images in foggy environment.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
HuiRong Zhang, Liang Fan, ChengJiu Liao, QiuMei Wang, and HuaChao Chen "A transmission line image defogging algorithm based on improved transmission estimation and color bias correction", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 127172A (21 July 2023); https://doi.org/10.1117/12.2685351
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KEYWORDS
Atmospheric modeling

Image transmission

Fiber optic gyroscopes

Detection and tracking algorithms

Video surveillance

Light scattering

Power grids

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