Abstract: To address the challenges of low-light images, including insufficient brightness, obscured details, and low contrast, this paper proposes a novel enhancement algorithm integrating an Improved Weighted Superposition Optimization (IWSO) algorithm with Inco-mplete Beta Function (IBF). Firstly, the standard WSO is enhanced by incorporating a good-point set initialization strategy to ensure uniform population distribution within the search space, and improves the algorithm by combining the positive cosine strategy and the greedy strategy to improve the convergence speed and accuracy of the algorithm. Secondly, the grayscale image is divided into bright regions and dark regions according to the threshold. The IWSO algorithm is applied to these two types of regions respectively, and image fusion is used to enhance the image contrast. Finally, the overall brightness of the enhanced image is corrected using an improved gamma function, thereby achieving the enhancement of the image's visual effect. Experimental results demonstrate that compared with other algorithms, the proposed algorithm not only effectively enhances the brightness, contrast, and details of images but also preserves their naturalness. It outperforms competing algorithms in overall enhancement performance, showcasing superior performance.