To address issues in sand-dust images, such as color shift, low clarity, and he poor performance of the dark channel prior method in handling sky regions, a sand-dust image enhancement method based on color cast correction and sky segmentation is proposed. First, the color cast in sand-dust images is corrected using a combination of channel compensation and the gray-world algorithm. Second, a dehazing method based on sky segmentation is proposed. The segmentation threshold is determined using information entropy, which separates the image into sky and non-sky regions. The dark channel is optimized using a fusion window. Then, an adaptive adjustment factor is introduced to refine the transmission map, and the atmospheric scattering model is employed to restore the image. Finally, in the HSV color space, an adaptive saturation enhancement algorithm and adaptive gamma correction are applied to adjust the image's saturation and brightness. Experimental results show that the proposed method can correct the color cast in sandstorm images, enhance image clarity, and improve restoration performance in sky regions. The method achieves improvements of 2.27%, 4.34%, and 0.25% in terms of average gradient, standard deviation, and information entropy, respectively.