激光雷达点云与可见光图像融合技术研究现状及展望
DOI:
CSTR:
作者:
作者单位:

1.中国航空工业集团公司北京长城计量测试技术研究所;2.上海大学通信与信息工程学院;3.清华大学 精密测试技术及仪器全国重点实验室;4.清华大学精密仪器系

作者简介:

通讯作者:

中图分类号:

基金项目:

国家“十四五” 计量技术基础科研项目


Research Status and Prospects of LiDAR Point Cloud and Visible-Light Image Fusion Technology
Author:
Affiliation:

1.AVIC Changcheng Institute of Metrology&2.Measurement

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    激光雷达点云与可见光图像融合技术,通过融合三维点云与二维纹理色彩信息,可以为环境感知提供更丰富、更精确的数据基础;单光子激光雷达相比于传统激光雷达,具有光子级灵敏度和皮秒级精度的优势,可实现远距离、低可观测场景下的高精度三维点云成像,与可见光图像的融合技术为解决复杂场景下的目标识别与定位问题提供了新路径。本文介绍了传统/单光子激光雷达系统、图像融合技术的基本原理,分析了传统/单光子激光雷达与可见光图像的特征差异及图像配准问题,阐述了传统/单光子激光雷达与可见光图像融合技术的研究及应用现状,最后对现阶段的传统/单光子激光雷达与可见光图像融合技术做出总结与展望。

    Abstract:

    Lidar point cloud and visible image fusion technology, by integrating three-dimensional point clouds with two-dimensional texture and color information, can provide a richer and more accurate data foundation for environmental perception. Compared to conventional LiDAR, single-photon LiDAR offers advantages such as photon-level sensitivity and picosecond-level timing precision, enabling high-precision three-dimensional point cloud imaging over long distances and in low-observability scenarios. The fusion technology of single-photon LiDAR with visible images provides a new pathway for addressing target recognition and localization challenges in complex environments. This paper introduces the fundamental principles of conventional/single-photon LiDAR systems and image fusion technology, analyzes the feature differences between conventional/single-photon LiDAR and visible images as well as the issue of image registration, elaborates on the research and application status of fusion technology between conventional/single-photon LiDAR and visible images, and finally summarizes and prospects the current state of conventional/single-photon LiDAR and visible image fusion technology.

    参考文献
    相似文献
    引证文献
引用本文
分享
相关视频

文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2025-10-27
  • 最后修改日期:2026-01-06
  • 录用日期:2026-01-07
  • 在线发布日期:
  • 出版日期:
文章二维码