Aiming at the problems of halo and color distortion in prior fog removal in dark channel, an image fog removal algorithm based on bright region segmentation is proposed. First, the foggy image is divided into bright areas and non-bright areas by brightness threshold segmentation and region growth. The formulas for calculating the transmittance of bright areas and non-bright areas are improved by using a bright channel prior and a super pixel, respectively. Then, the weighted fusion method is used to fuse the transmittance of these two areas to obtain a rough transmittance. Guided filtering is used to optimize them. At the same time, the foggy image is segmented by a quadtree. The average luminance of the final segmented area pixel is taken as the atmospheric light value, and the defog image is restored through the atmospheric scattering model. The experimental results show that the peak signal-to-noise ratio, the information entropy, the ratio of new visible edges and the gradient mean of the improved defog image are 6.5%, 2.1%, 5.5% and 5.3% higher than those of the original defog image. The improved algorithm can solve the problem of prior defogging in dark channel, and obtain clear and high contrast defogging images.