Abstract: In the complex environment, such as cloudy days, foggy days, night, weaker light illumination and other conditions, the image has a lack of contrast, and the whole is dark. In view of this problem, an image enhancement algorithm based on trigonometric function transformation and IRDPSO is proposed. The image enhancement method mainly consists of four steps. First, the color image is converted to a gray image. Then, the contrast of the grayscale image is improved by trigonometric function transformation. Then, the image is enhanced by the Laplacian operator. Finally, a color restoration process is applied to the image. Aiming at the parameters in trigonometric function transformation and the parameter selection problem of the Laplacian operator, the improved random drift particle swarm optimization (IRDPSO) algorithm is combined with an image enhancement algorithm, the fitness function is constructed by information entropy and image standard deviation, and the parameters are optimized. The proposed algorithm is compared with four other algorithms. The experimental results show that the proposed algorithm is simple, the image information entropy is enhanced, the standard difference is large, the color distortion of the image is small and the enhancement effect is better than that of the other algorithms, and the quality and contrast of the image are improved.