The detection of mine targets will be interfered by the underwater non-uniform strong noise (organic matter, suspended particles, etc). To solve this problem, a novel denoising method was proposed. Firstly, the local edge preserving filtering algorithm was optimized and the local edge preserving filtering based on edge perception constraint was proposed. A spatially adaptive edge perception constraint regularization term was introduced into the model to better represent the edges and details of the image, so that the edge-preserving and smoothing property could be better. Secondly, the multi-scale strategy was used to solve the heterogeneity of strong noise, the optimized model was iteratively applied to the noise removal results of each scale to generate multi-scale decomposition, and the denoising scale was gradually increaseed in the process of multi-scale decomposition. The noise of different scales was gradually separated from the denoising results of the previous scale. The experimental results show that, compared with other classical denoising methods, the proposed algorithm can better remove the underwater non-uniform strong noise while retaining the mine target information, which also has a certain guiding significance for real-time mine operation.