road extraction LiDAR remote sensing imagery information fus

  本文关键词：影像与LiDAR数据信息融合复杂场景下的道路自动提取，由笔耕文化传播整理发布。

影像与LiDAR数据信息融合复杂场景下的道路自动提取

Automatic Road Extraction in Complex Scenes Based on Information Fusion from LiDAR Data and Remote Sensing Imagery

[1] [2] [3] [4] [5]

LI Yijing1＇2, HU Xiangyun1 , ZHANG Jianqing1 , JIANG Wanshou3 , ZHANG Yongjun（1. School of Remote Sensing and Information Engineering, Wuhan University, Wuiqan 430079, China~

[1]武汉大学遥感信息工程学院,湖北武汉430079; [2]南昌大学建筑工程学院,江西南昌330031; [3]武汉大学测绘遥感信息工程国家重点实验室,湖北武汉430079

文章摘要：城区的道路自动提取受场景复杂度的影响一直是极具挑战的任务，尤其是阴影和遮挡较严重地区的道路提取难度较大。结合LiDAR数据和高分辨率遥感影像，提出一种自动道路提取方法。该方法首先对滤波后的点云强度信息获取初始道路中线及道路关键点；将地面点云强度、离散度及高分辨率遥感影像光谱数据多重信息融合建立道路模型，并以优化后的道路关键点作为种子点利用动态规划计算模型最优解，进一步提取道路网。试验表明，该方法在城市复杂场景下的自动提取主要道路是有效的。

Abstr：Automatic road extraction from remote sensing images in urban area has been a very challenging task due to the complexity of the scene, especially in the occluded or shadowed areas. An integrated method to fuse LiDAR data and high resolution imagery for automatic extraction of road centrelines is proposed. Firstly, theLiDAR point cloud is filtered to get the ground points whose intensity data is used to detect initial road centrelines and key points of the roads. A road model is then built on the intensity and dispersion of the ground points as well as spectral information obtained from the high resolution image. Based on the model, the dynamic programming algorithm is applied to find the optimal road centrelines linking the key points which are selected by evaluation. The experimental results indicate its effectiveness in automatic road extraction in urban and complex scenes.

文章关键词：

Keyword：:road extraction LiDAR remote sensing imagery information fusion dynamic programming

课题项目：国家自然科学基金（41171292;61172175）;国家973计划（2012CB719904）

作者信息：会员可见

  本文关键词：影像与LiDAR数据信息融合复杂场景下的道路自动提取，，由笔耕文化传播整理发布。