Underwater image descattering and quality assessment
Huimin Lu, Yujie Li, Xing Xu, Li He, Yun Li, Donald G. Dansereau, Seiichi Serikawa · 2016
Vision-based underwater navigation and object detection requires robust computer vision algorithms to operate in turbid water. Many conventional methods aimed at improving visibility in low turbid water. In this paper, we propose a novel contrast enhancement to enhance high turbid underwater images using descattering and color correction. The proposed enhancement method removes the scatter and preserves colors. In addition, as a rule to compare the performance of different image enhancement algorithms, a more comprehensive image quality assessment index Qu is proposed. The index combines the benefits of SSIM index and color distance index. Experimental results show that the proposed approach statistically outperforms state-of-the-art general purpose underwater image contrast enhancement algorithms. The experiment also demonstrated that the proposed method performs well for image classification.