Underwater Image Enhancement via Modeling White Degradation

The ability of underwater robots to accurately perceive their surroundings relies heavily on high-quality imaging systems. However, capturing clear images in aquatic environments is difficult due to light absorption and scattering challenges. Numerous studies have been conducted to develop underwater image enhancement techniques to address this issue, but striking a balance between computational speed, enhancement effect, and robustness remains a significant challenge. Our research takes a unique approach by analyzing the degradation of standard colors and utilizing the degradation of white as a priori information for our proposed adaptive color restoration and histogram equalization method. By modeling the difference in white color between air and underwater images, we estimate compensation coefficients via optimization to restore the color of underwater images. Our method achieves a superior balance of computational speed, color enhancement effect, and robustness compared with other state-of-the-art methods, as demonstrated by our experiments in various sea areas. This research significantly advances our understanding of underwater imaging and provides a practical solution for enhancing underwater images.