基于点云强度与颜色的机载雷达点云滤波方法

Airborne LiDAR point cloud filtering method based on point cloud intensity and color

提出一种基于点云强度与颜色属性的联合滤波方法,首先采用基于颜色的区域增长方法,将点云分成多个颜色相近的点云簇,然后联合点云的强度属性,将每个点云簇再进一步分组,最后依据统计学的相关方法,区分出地面层、植被层和建筑物层,并且结合实例,与不规则三角网渐进加密的点云滤波方法进行对比。结果表明,在不使用点云的几何信息情况下也可以对特定的地物进行分类,为点云滤波提供一个新的补充方法。

This paper proposes a joint filtering method based on point cloud intensity and color attributes.Firstly,the point cloud is divided into multiple point cloud clusters with similar colors by using the regional growth method based on color,and then each point cloud cluster is further grouped by combining the intensity attributes of the point cloud.Finally,the ground layer,vegetation layer and building layer are distinguished according to the relevant statistical methods.Combined with an example,it is compared with the point cloud filtering method for progressive encryption of triangular irregular networks.The results show that specific ground objects can be classified without using the geometric information of point cloud,which provides a new supplementary method for point cloud filtering.