Abstract: In the case of haze，aiming at the shortcomings of traditional fixed-value dark channel prior algorithm，such as low image quality and color distortion，an improved dark channel prior and particle swarm optimization algorithm is proposed. According to the characteristics of the particle swarm optimization algorithm，the best value of the retention factor in each average brightness range is optimized and brought into the dark channel prior algorithm. At the same time，the median filtering algorithm is used to replace the original two minimum filtering algorithm when solving the atmospheric light value. The experimental results show that the proposed algorithm has better subjective visual effect and objective evaluation criteria in image defogging compared with the traditional fixed value dark channel prior algorithm，and the operation speed of the algorithm is improved by about 14.3%.

Key words: images-defogging, dark channel prior, particle swarm optimization, median filtering algorithm