<p>Underwater images often suffer from color distortion, low contrast, and haze effects due to light absorption, scattering, and suspended particles in the water, which seriously affect the visual effect. To address these challenges, we propose an underwater image enhancement strategy based on color-corrected multi-scale fusion and dual-filter weighted detail enhancement (CMFD). Firstly, we design a color correction scheme. The scheme uses the proposed red channel compensation method to recover the attenuated red band information. Then the proposed adaptive clipping and luminance-aware white balance are used to eliminate the color deviation and obtain the color-corrected version of the map. Further, Contrast-Limited Adaptive Histogram Equalization (CLAHE) is performed on this basis to obtain the contrast-enhanced version of the image. Secondly, a new multi-scale fusion strategy is used, where the two versions of the image are fused by pyramid decomposition to fuse the weight maps of different features, utilizing their respective advantages to solve the limitations of a single version in processing underwater images. Finally, the proposed dual-filter weighted detail enhancement method is used to optimize the edges and suppress artifacts to obtain the final enhanced image. In order to validate the effectiveness of the CMFD designed in this paper, experiments are conducted on four underwater image datasets for qualitative and quantitative evaluations. Results demonstrate that our method effectively restores natural colors while enhancing image details and clarity. And the average values of several objective metrics surpass those of comparative methods.</p>