To overcome the color distortion in sky regions and large white regions brought by the dark channel prior dehazing algorithm, we propose a single image dehazing algorithm based on sparse representation model and feature extraction. Firstly, the algorithm learns the sparse features of foggy images via training sparse dictionary, and optimizes the sparse coefficients of the rough medium transmission image preliminarily. Then, the algorithm refines the medium transmission image by the sparse features of foggy gray images. Finally, with the converse solution of the degradation model, the algorithm obtains the dehazing image. The experimental results demonstrate that the proposed algorithm has obvious advantages in the processing of the sky area, and at the same time, it can recover more image details and marginal information.