Sonar images are prone to problems such as low contrast, low resolution, and edge distortion, so it is difficult to accurately separate effective signals from noise when removing noise from sonar images, resulting in reduced image contrast, unclear edge contours, and severe detail loss after denoising. Therefore, this paper proposes a sonar image denoising algorithm based on adaptive Wiener filtering and 2D-VMD. Firstly, a noisy image is decomposed using two-dimensional variational mode decomposition to obtain a series of sub modes with different center frequencies. Effective modal components are filtered out using correlation coefficients and structural similarity, and use adaptive Wiener filtering to process effective modal components, and finally reconstruct the filtered modal components to remove noise.The experimental results show that the proposed image denoising algorithm achieves the best results in terms of correlation coefficient and structural similarity, with a peak signal-to-noise ratio slightly lower than that of NSST domain denoising. Taking into account objective data and visual effects, the algorithm proposed in this paper achieves the best results in image details and edge preservation after removing noise.