4D点向地面激光扫描校准:对点云的放射性校准
Mansoor Sabzali1, Lloyd Pilgrim1
1Surveying Discipline, School of Engineering, University of Newcastle, Newcastle, NSW 2308, Australia.
Sensors (Basel, Switzerland)
|November 27, 2025
概括
这项研究通过使用基于纹理的LiDAR范围方程和神经网络来提高3D点云强度的准确性和精度来增强陆地激光扫描 (TLS). 这导致了对3D数据更可靠的第四维.
科学领域:
- 地理学工程 工程地质学
- 遥感 遥感 遥感 遥感
- 激光雷达技术 (LiDAR) 是一种技术.
背景情况:
- 陆地激光扫描仪 (TLS) 是一静态的LiDAR系统,可以同时测量几何和强度.
- 信号强度,即接收到传输功率的比率,表示反射强度和放射性不确定性.
- 激光雷达范围方程将信号强度与反射率和空间参数联系起来.
研究的目的:
- 为增强TLS点云强度开发基于纹理的LiDAR范围方程和神经网络方法.
- 通过解决反射率估计和空间变化来提高信号强度的准确性和精度.
- 为了在3D点云中确定强度作为可靠的第四维,反映固有的目标质量.
主要方法:
- 基于纹理的LiDAR范围方程的理论开发.
- 应用两步神经网络方法来增强强度.
- 使用四种不同的地面激光扫描仪 (Leica ScanStation P50,C10,RTC360和Trimble X9) 进行验证.
主要成果:
- 在测试的设备中,在点云强度方面取得了显著的改进.
- 颜色强度的精度提高了至少40%.
- 颜色强度的精度提高了至少97%.
结论:
- 开发的方法提高了TLS点云强度的准确性和精度.
- 这项研究使得4D TLS点云校准框架能够用于标准化的放射值.
- 这些发现支持对影响LiDAR测量的目标属性的进一步调查.
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