A hue contrast enhancement algorithm based on gene expression programming optimization is proposed. A number of low illumination images are selected as the reference images and the results are compared with those of the adaptive histogram equalization, homomorphic filtering, multiscale Retinex enhancement, and color-restored multiscale Retinex enhancement. The average values of the peak signal-to-noise ratio, structural similarity and quality index based on local variance of the proposed algorithm are 25.93, 0.75, and 0.87, respectively, which are better than the other algorithms. Subjectively, the brightness and contrast of images processed by the propose method are more natural and more in line with human visual characteristics. The proposed algorithm can be widely applied to the field of machine vision in low illumination environments.