Dark channel prior dehazing algorithm based on bilateral filter

Under harsh weather conditions, visual inspections of power systems face significant challenges due to low image quality and difficulty in recognition. To address this issue, we propose a dark channel prior dehazing algorithm based on bilateral filtering. This algorithm effectively removes the haze effects from images and is compared with traditional image enhancement methods such as histogram equalization and Retinex enhancement. Experimental results show that the proposed algorithm not only reduces computational cost but also demonstrates higher robustness in natural scene image processing. In adverse environments such as rain and fog, the algorithm significantly improves image clarity and contrast. The algorithm holds strong practical application value, especially in remote visual inspections and fault detection for power equipment.