This study focuses on the problem of a priori blind zone, which is generated by the current single-frame haze image restoration algorithm using a single prior. To address this problem, a haze image restoration algorithm using multiple prior constraints is proposed. First, the saturation prior is proposed, and the defined adjustment coefficient is used to simplify the process of solving the rough transfer diagram. Second, in the Markov random field model, the color attenuation prior is used to constrain and optimize the adjustment coefficient to obtain an accurate transfer diagram. Then, the light and dark pixels are used to obtain accurate atmospheric light a priori. Finally, the fog-free image is restored. Experimental results reveal that compared with other algorithms, Compared with the proposed algorithm, other algorithms have reduced the effective detail intensity by 24.9%, 51.4%, 41.5%, and 39.3%, respectively, and the hue reproduction has decreased by 21.4%, 24.8%, 24.1%, and 29.5%, respectively. The proposed algorithm successfully restores the image. Consequently, the effective detail information in the image becomes rich, and the color tone becomes natural. Moreover, it enables the image to have strong applicability.