A Hybrid Framework for Underwater Image Enhancement

• Main Authors: Xinjie Li, Guojia Hou, Lu Tan, Wanquan Liu
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Hybrid framework; dehazing; underwater white balance; variational contrast and saturation enhancement
• Online Access: https://ieeexplore.ieee.org/document/9242235/

Underwater captured images often suffer from poor visibility caused by two major degradations: scattering and absorption. In this paper, we propose a hybrid framework for underwater image enhancement, which unifies underwater white balance and variational contrast and saturation enhancement. In our framework, the improved underwater white balance (UWB) algorithm is integrated with histogram stretching, aiming to better compensate the attenuation difference along the propagation path and remove undesired color castings. In addition, a variational contrast and saturation enhancement (VCSE) model is developed based on the enhanced result obtained from UWB. The advantages of VCSE model lie in the improvements of contrast and saturation as well as the elimination of hazy appearance induced by scattering. Moreover, we design a fast Gaussian pyramid-based algorithm to speed up the solving of VCSE model. The improvements achieved by our method include the more effective in color correction, haze removal and detail clarification. Extensive qualitative and quantitative assessments demonstrate that the proposed approach obtains high quality outcomes, which outperforms several state-of-the-art methods. Application tests further verify the effectiveness and broad application prospects of our proposed method.