Objective Aiming at the problem that the underwater images in the industrial environment are affected by suspended solids in water resulting in low image clarity and high contrast an underwater image enhancement algorithm based on linear weighting of image entropy was proposed. Methods The algorithm linearly weighted the white balance algorithm histogram equalization algorithm and dark channel prior algorithm based on the image entropy theory and then determined the adjustment coefficient to output high-quality images through the experimental environment. Through taking images in different underwater environments at depths of 1 m 1. 5 m and 2 m the obtained underwater images were compared and processed by using the above three algorithms and this algorithm. The processing results were evaluated by PSNR and UIQM as evaluation indicators. Results The experimental results showed that the proposed algorithm judged by the PSNR index improved the underwater image quality by 22. 81% for the water depth of 1m 46. 67% for the water depth of 1. 5 m 38. 94% for the water depth of 2 m and improved the combined image quality by 36. 14% on average compared with the other three algorithms. The proposed algorithm judged by the UIQM index improved the image quality by 1. 02% for the water depth of 1m 0. 73% for the water depth of 1. 5 m 1. 82% for the water depth of 2 m and improved the combined image quality by 1. 19% on average compared with the other three algorithms. Conclusion It can be proved that the proposed algorithm has significantly improved the image definition compared with other traditional algorithms and this algorithm can adapt to different depths of underwater environments providing a new solution for underwater image enhancement in industrial environments.