Fusion of airborne lidar point cloud and imagery captured from integrated sensor system

Xiangyun Hu, Lizhi Ye, Xiaokai Li, Junfeng Zhu, H. Long
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引用次数: 2

Abstract

By fusing with other sensory data, especially high resolution imagery, LiDAR can be a good source of information for DEM extraction and feature extraction because it provides integrated information of geometric (surface), spectral and spatial property. Nowadays airborne LiDAR system vendors such as Leica and Toposys and others are providing systems with integrated camera capturing 3D point cloud and high resolution images simultaneously, for example, Leica's ALS50II, ALS60, and Toposys' FALCON II. The full potential of an integrated system in surveying and mapping has to be explored yet. In this paper, taking example of Toposys' FALCON data, we discuss some issues of data fusion: (1) cross sensor data registration, including geometric error budget; (2) two methods of fused data generation - imagery fused with range image re-sampled from point cloud and point cloud with assigned image pixel attributes. (3) Occlusion problem and how to solve it. We also show the segmentation results by a combined segmentation algorithm carried out on the fused multiple layer data. The results demonstrate the advantages of data fusion due to rich information and cues of objects in the fused data.
机载激光雷达点云和集成传感器系统捕获图像的融合
通过与其他感官数据,特别是高分辨率图像的融合,LiDAR可以提供几何(表面)、光谱和空间属性的综合信息,可以成为DEM提取和特征提取的良好信息来源。如今,机载激光雷达系统供应商,如徕卡和Toposys等,都在提供集成摄像头的系统,同时捕获3D点云和高分辨率图像,例如,徕卡的ALS50II, ALS60,和Toposys的猎鹰II。一个综合的测绘系统的全部潜力还有待探索。本文以Toposys的FALCON数据为例,讨论了数据融合的一些问题:(1)跨传感器数据配准,包括几何误差预算;(2)融合数据生成的两种方法——从点云重采样的距离图像融合图像和赋值图像像素属性的点云融合图像。(3)遮挡问题及解决方法。并给出了对融合多层数据进行组合分割的结果。结果表明,融合后的数据具有丰富的目标信息和线索,具有数据融合的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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