ing at the problems of the halo phenomenon and inaccurate selection of atmospheric light values in dark channel prior algorithm, an image dehazing method based on dark channel compensation and improvement of atmospheric light value is proposed in this paper. In order to weaken the halo effect at the edge of the image scene, a solution based on the dark channel compensation model is proposed first, the halo region is identified by the weighted channel difference method, and then the dark channel values of this region are modified by corrosion, fusion, and other treatment. It is linearly fused with the original dark channel images to compensate the dark channel. For the problem of inaccurate selection of atmospheric light value, the quadtree segmentation method is improved, with the strategy of adjacent region comparison added. Hence, the proposed method can obtain more accurate atmospheric light values, leading to more clear and natural restored images with more details. Finally, the haze-free image is restored by means of the atmospheric scattering model and the optimized transmittance. The experimental results show that the proposed method can effectively remove the halo effect and obtain the atmospheric light value accurately.