The pixel position of the haze-line endpoint is not accurate enough in the non-local prior dehazing algorithm.To resolve this problem,an image dehazing algorithm based on non-local prior with an optimized haze-line was proposed in this study.We analyzed haze-line theory and combined the dark channel theory to find the real haze-line endpoint of the largest cluster.Then,we took it as the known conditions to compensate the maximum distance between other haze-line endpoints of small cluster and the atmospheric light. According to the different pixels in the class and the corresponding angles,the haze-line endpoint of individual pixel was estimated,and then,the transmission of every pixel after optimization was refined.Finally,local grey value difference fusion dark channel prior (DCP) and non-local prior transmission was used to produce our transmission map.We compared our algorithm with three existing algorithms by applying them to multiple outdoor hazy images through subjective and objective analyses.The experimental results demonstrate that proposed algorithm has a better dehazing effect, especially in the sky region,the image restoration effect is more prominent.