摘要
针对海洋环境复杂、水体光学性质特殊、数据收集困难以及单目光学图像结构化信息不全等关键问题,对近年重要的水下单目光学图像三维重建相关设备及理论方法进行了总结和分析,从3个方面剖析了水下单目光学图像的三维重建依然存在的问题,包括单目光学设备成熟度有待提升、水下单目光学物理性质研究不足、重建结果边缘精确度有待提升等。针对关键问题研制了水下光学距离选通相机设备,研究了基于深度学习的单目光学图像三维重建算法,据此总结了单目光学图像的水下场景三维重建未来可能的关键技术。
In response to key challenges including the complexity of marine environments,the unique optical properties of water bodies,difficulties in data collection,and the lack of structured information in monocular optical images,this paper summarizes and analyzes recent significant advancements in equipment and theoretical methods related to 3D reconstruction of underwater monocular optical images.It dissects the existing issues in 3D reconstruction from three aspects:the need for enhanced maturity of monocular optical devices,insufficient research on the physical properties of underwater monocular optics,and the need for improved edge precision in reconstruction results.Addressing these key issues,we developed an underwater optical range-gated camera device and further studied a monocular optical image 3D reconstruction algorithm based on deep learning.This paper proposes potential key technologies for future 3D reconstruction of underwater scenes using monocular optical images.
作者
李双全
张奇贤
姚海洋
李旭东
米建军
LI Shuangquan;ZHANG Qixian;YAO Haiyang;LI Xudong;MI Jianjun(System Department one,Xi’an Institute of Applied Optics,Xi’an 710065,China;School of Electronic Information and Artificial Intelligence,Shaanxi University of Science and Technology,Xi’an 710021,China)
出处
《激光杂志》
CAS
北大核心
2024年第11期93-99,共7页
Laser Journal
基金
国家自然科学基金青年项目(No.62301302)。
关键词
水下光学图像
三维重建
单目图像
深度学习
underwater optical images
3D reconstruction
monocular images
deep learning
