Single underwater image enhancement based on differential attenuation compensation

Frontiers in Marine Science

Marine Science

Zhe Xuanyuan¹  Yunting Lai²  Jiongjiang Chen²  Jialin Tang²  Wanxin Liang²  Binghua Su²  Jinghui Yan²  Zhuang Zhou² 

[1] Hong Kong Baptist University United International College, Beijing Normal University, Zhuhai, China;Key Laboratory of Intelligent Detection in Complex Environment of Aerospace Land and Sea, Beijing Institute of Technology, Zhuhai, China;

关键词: underwater image;    image enhancement;    contrast stretching;    differential attenuation compensation;    machine vision;   

DOI  :  10.3389/fmars.2022.1047053

 received in 2022-09-17, accepted in 2022-10-17,  发布年份 2022

来源: Frontiers

【 摘 要 】

High quality underwater images and videos are important for exploitation tasks in the underwater environment, but the complexity of the underwater imaging environment makes the quality of the acquired underwater images generally low. To correct the chromatic aberration and enhance the sharpness of underwater images in order to improve the quality of underwater images, we based on the differential compensation proposed a Differential Attenuation Compensation (DAC) method. The underwater image is contrast stretched to improve the contrast of the image, as well as the underwater image is denoised, for the red channel with serious loss of detail information we choose the blue and green channels with more detail information to compensate for this, and finally the image is restored through the grayscale world to obtain more realistic colors. Our method is qualitatively and quantitatively compared with multiple state-of-the-art methods in the public underwater image dataset, underwater image enhancement benchmark (UIEB) and enhancing underwater visual perception (EUVP), demonstrating that the underwater images processed by our method better resolve the problems of chromatic aberration and blur, with more realistic color, detail and better underwater image quality evaluation indicators

【 授权许可】

Unknown   
Copyright © 2022 Lai, Zhou, Su, Xuanyuan, Tang, Yan, Liang and Chen