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基于稀疏和稠密图像匹配与对极约束的树高提取改进算法

蔡翔远 陈晓桐 李荣昊 魏江南 李帅 赵红颖

蔡翔远, 陈晓桐, 李荣昊, 魏江南, 李帅, 赵红颖. 基于稀疏和稠密图像匹配与对极约束的树高提取改进算法[J]. 全球定位系统, 2024, 49(3): 87-93. doi: 10.12265/j.gnss.2023221
引用本文: 蔡翔远, 陈晓桐, 李荣昊, 魏江南, 李帅, 赵红颖. 基于稀疏和稠密图像匹配与对极约束的树高提取改进算法[J]. 全球定位系统, 2024, 49(3): 87-93. doi: 10.12265/j.gnss.2023221
CAI Xiangyuan, CHEN Xiaotong, LI Ronghao, WEI Jiangnan, LI Shuai, ZHAO Hongying. Improved algorithm for tree height extraction based on sparse and dense image matching with epipolar constraints[J]. GNSS World of China, 2024, 49(3): 87-93. doi: 10.12265/j.gnss.2023221
Citation: CAI Xiangyuan, CHEN Xiaotong, LI Ronghao, WEI Jiangnan, LI Shuai, ZHAO Hongying. Improved algorithm for tree height extraction based on sparse and dense image matching with epipolar constraints[J]. GNSS World of China, 2024, 49(3): 87-93. doi: 10.12265/j.gnss.2023221

基于稀疏和稠密图像匹配与对极约束的树高提取改进算法

doi: 10.12265/j.gnss.2023221
基金项目: 国家自然科学基金(42130104)
详细信息
    作者简介:

    蔡翔远:(1999—),男,硕士,研究方向为遥感图像处理与应用、三维点云信息处理. E-mail:xycai@pku.edu.cn

    陈晓桐:(1995—),女,硕士,研究方向为遥感图像处理与应用、三维图像可视化. E-mail:2101210112@stu.pku.edu.cn

    李荣昊:(1997—),男,硕士,研究方向为遥感图像处理与应用、遥感图像拼接. E-mail:ronghao.li@stu.pku.edu.cn

    魏江南:(2000—),男,硕士,研究方向为遥感图像处理与应用、无人机智能升降. E-mail:wjn@pku.edu.cn

    赵红颖:(1971—),女,副教授,研究方向为遥感图像处理与应用、无人机航空遥感技术. E-mail:zhaohy@pku.edu.cn

    通讯作者:

    赵红颖 E-mail:zhaohy@pku.edu.cn

  • 中图分类号: P228;P231

Improved algorithm for tree height extraction based on sparse and dense image matching with epipolar constraints

  • 摘要: 树高是监测森林状况的重要参数,摄影测量法具有低成本、灵活的特性,是树高采集的重要方法之一. 作为一种被动遥感方式,传统的摄影测量方法往往需要数量较多,重叠率较高的图像数据,这与传统图像特征的稀疏性有关. 为了提高图像数量受限条件下的树高提取精度,提出将稀疏特征匹配和稠密像素匹配相结合,并使用对极约束过滤外点的方法,得到稠密且精度较高的匹配结果,并通过三维重建算法得到森林场景点云. 该方法在少量图像的情况下就可以较为完整地重建森林场景并提取树高,将提取的树高与机载激光雷达(light detection and ranging,LiDAR)点云的结果进行对比,相关系数为0.91,最大误差为1.64 m. 该算法只需要少量的重叠图像,这表明了该算法在处理高分辨率卫星图像方面具有一定潜力.

     

  • 图  1  树木重建与树高提取算法

    图  2  图像匹配结果

    图  3  对极约束

    图  4  点云重建结果对比

    表  1  树高对比结果

    统计指标
    相关系数 0.91
    最大误差/m 1.64
    最小误差/m 0.03
    平均误差/m 0.91
    LiDAR点云中提取的最大树高/m 21.60
    LiDAR点云中提取的最小树高/m 16.70
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-12-04
  • 录用日期:  2023-12-04
  • 网络出版日期:  2024-04-19

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