首页|基于高光谱激光雷达的多视角木叶三维重建研究

基于高光谱激光雷达的多视角木叶三维重建研究

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  • 国家科技期刊平台
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高光谱激光雷达(HSL)能实现空间-光谱信息的同步采集，为树木的木叶三维重建提供了可能。利用自研的HSL系统获取不同视角的树木点云数据，进行了多视角下的木叶分离，并根据分离结果完成了的木叶三维重建。针对传统最近邻迭代(ICP)算法严格的点云初始条件需求，提出了改进的点云配准方法。首先，采用快速点特征直方图(FPFH)描述点云的局部特征，然后基于随机抽样一致性(RANSAC)算法实现不同视角点云的粗配准，最后利用ICP算法实现精配准。在选出特征通道的基础上，利用随机森林(RF)和支持向量机(SVM)完成木叶分离，最终完成木叶三维重建。实验表明，在15°和30°的视角差下，提出的改进点云配准方法均达到较好的配准精度，同时基于特征通道选择的RF方法木叶分离准确度分别达到98。17%和98。87%。
Research of multi-view wood-leaf 3D reconstruction based on hyperspectral lidar
Hyperspectral lidar(HSL)can obtain spatial and spectral information simultaneously,which provides more possibilities for three-dimention(3D)reconstruction of wood-leaf.The multi-view tree point clouds were collected using a self-developed HSL system for wood-leaf separation and 3D reconstruction.In order to meet the strict condition of traditional iterative closest point(ICP)algorithm,an improved point cloud registration method was proposed in this work.Firstly,the local feature of every point was described using fast point feature histogram(FPFH).Then,rough and accurate registration of point clouds were successively conducted based on random sample consensus(RANSAC)algorithm and ICP algorithm respectively.Finally,the wood and leaf components were separated based on the spectral data of the registered point clouds,the feature bands were extracted for wood and leaf separation on the basis of the spectral feature channel selection with random forest(RF)algorithm and support vector machine(SVM)algorithm,and 3D reconstruction of wood-leaf components was completed based on separation under different view.The experiment results show that the proposed improved point cloud registration method can achieve excellent registration accuracy both under 15° and 30° view angle difference,and the corresponding separation accuracy using RF algorithm based on feature channel selection reaches 98.17%and 98.87%,respectively.

remote sensinghyperspectral lidarspatial-spectral information3D reconstruction

曹铮、邵慧、孙龙、胡玉霞、陈杰、徐恒、陈冲

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安徽建筑大学电子与信息工程学院,安徽 合肥 230601

安徽省古建筑智能感知与高维建模国际联合研究中心,安徽 合肥 230601

遥感 高光谱激光雷达 空间-光谱信息 三维重建

红外与低温等离子体安徽省重点实验室开放课题安徽省住房城乡建设科学技术计划项目浙江省海洋大数据挖掘与应用重点实验室开放课题安徽省高校省级自然科学研究项目安徽省高校省级自然科学研究项目

IRKL2023KF042022-YF077OBDMA2021032023AH050181KJ2021JD16

2024

10.3969/j.issn.1007-5461.2024.04.010

量子电子学报
中国光学学会基础光学专业委员会 中国科学院合肥物质科学研究院

量子电子学报

CSTPCD北大核心
影响因子：0.67
ISSN：1007-5461
年,卷(期)：2024.41(4)
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