For solving the problems of exposure imbalance and low contrast ratio in photogrammetry and visible light remote sensing, as well as the standard automatic color equalization algorithm, which does not fully take into account the color characteristics of some regions,this paper improves the standard automatic color equalization algorithm based on the non-circulating lateral inhibition model that simulate human visual characteristics and Gaussian distribution. The corrected luminance value of the target point is calculated by using the non-circulating lateral inhibition network model, and the Gaussian distribution is used to select the sampling points with higher correlation, which reduces the complexity of the algorithm. Three images with different color defects were compared, using standard automatic color equalization algorithm and improved ones. The experimental results show that the mean value of the images is more reasonable and the important parameters such as standard deviation and entropy are improved compared with the original algorithm. The standard deviation is about 15% improvement. The experimental results show that the improved algorithm has obvious color balance effect and visual effect.