Optimization of Transmission Line Image Dehazing Method under Harsh Conditions

With industrialisation and soil desertification in some areas, haze and sandstorm weather occur frequently in winter, posing challenges to transmission line image recognition monitoring equipment. In this study, guided filtering and gamma correction methods are introduced to optimize the problems of long calculation time and post-processing tone shift in the current popular He method based on dark channel prior. The foggy images captured by transmission line monitoring equipment under different working conditions in recent years are used for simulation, and the study shows that the He method based on the dark channel a priori has significantly improved the computation speed after the bootstrap filter, and the brightness has been improved after the gamma correction, which can be used as a reference for the theoretical research and practical application of the fog removal of transmission line on-line monitoring images.