基于视觉同时定位与地图构建的水下图像增强式视觉三维重建方法

doi:10.3969/j.issn.1004-132X.2024.02.011

中国机械工程 ›› 2024, Vol. 35 ›› Issue (02): 268-279.DOI: 10.3969/j.issn.1004-132X.2024.02.011

基于视觉同时定位与地图构建的水下图像增强式视觉三维重建方法

梅杰1,2,3;覃嘉锐1,2;陈定方2;陈昆1,2

1.武汉理工大学交通与物流工程学院，武汉，430063
2.武汉理工大学智能制造与控制研究所，武汉，4300633.武汉理工大学港口货物装卸技术交通部重点实验室，武汉，430063

出版日期:2024-02-25 发布日期:2024-04-12
作者简介:梅杰，男，1985年生，副教授。研究方向为微纳机电系统、仿生机器人路径规划与导航。发表论文25篇。E-mail:meijieben@foxmail.com。
基金资助:
国家自然科学基金(5180051287)

SLAM-based Underwater Image Enhanced Visual 3D Reconstruction Method

MEI Jie1,2,3;QIN Jiarui1,2;CHEN Dingfang2;CHEN Kun1,2

1.School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan,430063
2.Institute of Intelligent Manufacturing and Control,Wuhan University of Technology,Wuhan,430063
3.Key Laboratory of Port Cargo Handling Technology of Wuhan University of Technology,
Wuhan,43006

Online:2024-02-25 Published:2024-04-12

摘要/Abstract

摘要： 针对仿生机器鱼水下作业时面临的水下图像质量偏低、水下自主定位难的问题，提出一种颜色均衡与G-B通道先验融合的水下图像增强式算法。将该算法和视觉同时定位与地图构建(SLAM)方法结合，实现了水下图像增强式的视觉三维重建。在不同水域环境下进行了水下图像处理实验、水下环境视觉三维重建实验和运动轨迹跟踪实验，结果表明该方法有效提高了水下图像综合质量，特征匹配效率提高了16.03%，真实轨迹与估计轨迹的误差平均约为7.99 mm。

关键词: 水下图像增强, 三维重建, 运动轨迹跟踪, 视觉同时定位与地图构建(SLAM)

Abstract: Regarding with problems of low quality of underwater images and difficulty of underwater autonomous localization faced by bionic robotic fish in underwater operations, an enhanced underwater image algorithm with color equalization and a priori fusion of G-B channels was proposed. The algorithm was combined with visual SLAM construction methods to enhance visual 3D reconstruction of underwater images. Underwater image processing experiments, underwater environment visual 3D reconstruction experiments, and motion trajectory tracking experiments were carried out in different water environments. The results show that the method effectively improves the comprehensive quality of underwater images. The feature matching efficiency is improved by 16.03%, and the error between the real trajectory and the estimated trajectory is about 7.99 mm on average.

Key words: underwater image enhancement, 3D reconstruction, trajectory tracking, visual simultaneous localization and mapping(SLAM)

中图分类号:

梅杰, 覃嘉锐, 陈定方, 陈昆, . 基于视觉同时定位与地图构建的水下图像增强式视觉三维重建方法[J]. 中国机械工程, 2024, 35(02): 268-279.

MEI Jie, QIN Jiarui, CHEN Dingfang, CHEN Kun, . SLAM-based Underwater Image Enhanced Visual 3D Reconstruction Method[J]. China Mechanical Engineering, 2024, 35(02): 268-279.

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链接本文: http://www.cmemo.org.cn/CN/10.3969/j.issn.1004-132X.2024.02.011

http://www.cmemo.org.cn/CN/Y2024/V35/I02/268

参考文献

［1］MACARIO BARROS A, MICHEL M, MOLINE Y, et al. A Comprehensive Survey of Visual Slam Algorithms［J］. Robotics, 2022, 11(1):24-51.
［2］WANG X, FAN X, SHI P, et al. An Overview of Key SLAM Technologies for Underwater Scenes［J］. Remote Sensing, 2023, 15(10):2496.
［3］RAO B S. Dynamic Histogram Equalization for Contrast Enhancement for Digital Images［J］. Applied Soft Computing, 2020, 89:106114.
［4］ULUTAS G, USTUBIOGLU B. Underwater Image Enhancement Using Contrast Limited Adaptive Histogram Equalization and Layered Difference Representation［J］. Multimedia Tools and Applications, 2021, 80:15067-15091.
［5］REZA A M. Realization of the Contrast Limited Adaptive Histogram Equalization(CLAHE) for real-time image enhancement［J］. Journal of VLSI Signal Processing Systems for Signal, Image and Video Technology, 2004, 38:35-44.
［6］马敏慧,王红茹,王佳. 基于改进的MSRCR-CLAHE融合的水下图像增强算法［J］. 红外技术,2023,45(1):23-32.
MA Minhui, WANG Hongru, WANG Jia. Underwater Image Enhancement Algorithm Based on Improved MSRCR-CLAHE Fusion［J］. Infrared Technology, 2023, 45(1):23-32.
［7］李广豪, 席志红. 基于图像融合的水下光照不均匀图像增强算法［J］. 计算机仿真,2023,40(4):330-335.
LI Guanghao, XI Zhihong. Underwater Illumination Inhomogeneity Image Enhancement Algorithm Based on Image Fusion［J］. Computer Simulation,2023,40(4):330-335.
［8］PETKOVA L, DRAGANOV I. Noise Adaptive Wiener Filtering of Images［C］∥2020 55th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST). Serbia， 2020:177-180.
［9］ANAN S, KHAN M I, KOWSAR M M S, et al. Image Defogging Framework Using Segmentation and the Dark Channel Prior［J］. Entropy, 2021, 23(3):285-312.
［10］龚万齐,冯常. 基于改进暗通道的水下图像快速复原［J］. 计算机工程与设计,2022,43(7):2015-2021.
GONG Wanqi, FENG Chang. Rapid Underwater Image Restoration Based on Improved Dark Channel［J］. Computer Engineering and Design,2022,43(7):2015-2021.
［11］ZHOU J, LIU D, XIE X, et al. Underwater Image Restoration by Red Channel Compensation and Underwater Median Dark Channel Prior［J］. Applied Optics, 2022, 61(10):2915-2922.
［12］LI B, MA H, LI J. Design and Realization of Underwater Target Vision 3D Reconstruction System［C］∥2022 IEEE International Conference on Mechatronics and Automation (ICMA). Guilin， 2022:467-474.
［13］HUO G, WU Z, LI J, et al. Underwater Target Detection and 3D Reconstruction System Based on Binocular Vision［J］. Sensors, 2018, 18(10):3570-3601.
［14］HOU J, YE X. Real-time Underwater 3D Reconstruction Method Based on Stereo Camera［C］∥2022 IEEE International Conference on Mechatronics and Automation (ICMA). Guilin， 2022:1204-1209.
［15］魏郭依哲, 陈思遥, 刘玉涛, 等. 水下图像增强和修复算法综述［J］. 计算机应用研究, 2021, 38(9):2561-2569.
WEI Guoyizhe, CHEN Siyao, LIU Yutao, et al. Survey of Underwater Image Enhancement and Restoration Algorithms［J］. Application Research of Computers, 2021, 38(9):2561-2569.
［16］王霞, 左一凡. 视觉SLAM研究进展［J］. 智能系统学报, 2020, 15(5):825-834.
WANG Xia, ZUO Yifan. Research Progress on Visual SLAM［J］. Journal of Intelligent Systems, 2020, 15(5):825-834.
［17］余卓平,鞠然,韩燕群,等. 融合车辆动力学的双目视觉惯性SLAM研究［J］. 华中科技大学学报（自然科学版）,2022,50(11):85-89.
YU Zhuoping, JU Ran, HAN Yanqun, et al. Study on Binocular Vision Inertial SLAM Based on Vehicle Dynamics［J］. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2022, 50(11):85-89.
［18］HIRSCHMULLER H. Accurate and Efficient Stereo Processing by Semi Global Matching and Mutual Information［C］∥Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Washington DC, 2005:807-814.
［19］GEIGER A, ROSER M, URTASUN R. Efficient Large-scale Stereo Matching［C］∥Asian Conference on Computer Vision. Queenstown, 2010:25-38.
［20］王子昂,李刚,刘秉琦,等. 超大视场长波红外立体视觉外部参数标定及内外参数评价［J］. 光谱学与光谱分析,2020,40(9):2670-2675.
WANG Ziang, LI Gang, LIU Bingqi. Calibration of External Parameters and Evaluation of Internal and External Parameters of Long-wave Infrared Stereo Vision with Large Field of View［J］. Spectroscopy and Spectral Analysis,2020,40(9):2670-2675.

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[5]	张辉;张丽艳;韦虎;. 双目立体测量系统标定的三步法[J]. J4, 2009, 20(16): 0-2015.

基于视觉同时定位与地图构建的水下图像增强式视觉三维重建方法

SLAM-based Underwater Image Enhanced Visual 3D Reconstruction Method

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