Specular Reflection Image Enhancement Based on a Dark Channel Prior
In this paper, we propose a specular highlight image enhancement algorithm based on a dark channel prior to solve the problem of information loss in specular highlight images in real scenes. First, the algorithm is based on the dark channel prior algorithm, and a moving window minimum filter is used to estimate the global illumination component. Then, a weighted function based on the local pixel color difference is introduced to solve the halo artifacts in the image. Then, the improved guided filter algorithm is used to optimize the transmittance, which improves the computational efficiency of the algorithm. Finally, the brightness of the image is adjusted by the CLAHE algorithm to enhance the local details of the image. Experimental results show that this method can effectively enhance the information in specular highlight images, and its processing results are obviously better than those of other algorithms.