An Underwater Image Enhancement Algorithm Based on Improved MSRCR-CLAHE Fusion

To address the problems of color fading and low contrast in underwater images caused by the complex imaging environment in the ocean, improved Multi-Scale Retinex with Color Restore (MSRCR) and Contrast Limited Adaptive Histogram Equalization (CLAHE) multi-scale fusion algorithms for underwater image enhancement are proposed. First, the MSRCR algorithm with guided filtering was used to solve the problem of underwater image color fading. Second, the CLAHE algorithm with Gamma correction was used to improve the contrast of underwater images. Finally, the improved MSRCR and CLAHE images were fused at multi-scale to obtain an underwater image with enhanced detail. The experimental results show that, compared with other algorithms, the Peak Signal-To-Noise Ratio (PSNR) of the proposed algorithm is improved by 9.3914 on average, and the Structural Similarity Index Measure (SSIM) and Underwater Image Quality Evaluation (UIQE) increased by 0.3013 and 4.7047 on average, respectively, which can realize the effective enhancement of underwater images.