Intelligent Defogging Method Based on Clustering and Dark Channel Prior

Abstract

In view of the foggy images collected by outdoor vision system are blurred, an intelligent defogging method based on clustering and dark channel prior is proposed. This method improves the traditional K-means clustering algorithm, considering the correlation between the samples and the running time of the algorithm, using the improved K-means clustering algorithm to recognize the foggy images; The traditional defogging algorithm based on dark channel prior is enhanced from the angle of improving the adaptability and efficiency of the algorithm, as well as improving the defogging effect, the clearness of the foggy images is realized based on the enhanced defogging algorithm. The Simulation results show that the proposed method can automatically recognize and process the foggy images, the recognition accuracy of the foggy images is high and the defogging effect is good, which is beneficial to improve the reliability of the outdoor vision system.