In the process of underwater imaging, the light source is one of the key factors affecting image quality owing to the scattering and absorption of light. This results in many problems such as color distortion, low contrast, and visibility of underwater images. Underwater images with degraded quality are not conducive to analysis and utilization. To address these problems, we propose an underwater image-enhancement algorithm based on color correction and dark–bright dual-channel prior. First, a color-compensation algorithm based on the standard deviation ratio is proposed to effectively solve the color-distortion problem. Sharpening is used to enhance the details and edges of the image to obtain a contrast-enhanced image. Conversely, we propose a dark and bright dual-channel to remove image blur based on channel-difference weighting to obtain a visibility-restored image. Finally, a multiscale fusion method is used to fuse the contrast-enhanced and visibility-restored images based on the weights. The proposed algorithm is compared with other underwater image enhancement algorithms for qualitative and quantitative evaluations. Experimental results show that the proposed algorithm can effectively eliminate color deviations and restore image clarity. The enhanced images generated are better than those generated by other algorithms in terms of Undewater Color Image Quality Evaluation(UCIQE), Underwater Image Quality Measurement (UIQM) andInformation Entropy(IE) parameter indices. Underwater images are of high quality owing to the scattering and absorption of underwater light.