High-Turbidity Underwater Image Enhancement via Turbidity Suppression Fusion

Underwater operations frequently encounter turbid environments, where light absorption and scattering by suspended particles degrade image quality by causing color distortion, uneven brightness, and blurred details. Clear imaging in such conditions is essential for enhancing the efficiency and effectiveness of underwater tasks, including exploration, marine ecological monitoring, and the preservation of underwater cultural heritage. However, existing underwater image enhancement methods struggle to perform well in turbid waters, especially in highly turbid conditions. In this study, we present an advanced method designed to significantly improve the clarity of images captured in turbid water. We begin by introducing an adaptive color correction algorithm that uses the dominant color channel’s pixel values to adjust and restore the colors of other channels, mitigating color distortion in turbid conditions. Subsequently, we apply adaptive threshold segmentation and turbidity assessment to automatically calibrate histogram equalization, which enhances local contrast and suppresses noise. Finally, we develop a dark channel prior based on turbidity background light estimation, which further improves color restoration and detail recovery. Our proposed method outperforms existing state-of-the-art techniques in color restoration, turbidity removal, and detail enhancement. Experimental results demonstrate that our approach effectively enhances imaging performance in turbid waters, thereby significantly improving the operational efficiency of various underwater applications.