一种融合曲度的自适应八叉树点云压缩算法  

An Adaptive Octree Point Cloud Compression Algorithm with Curvature Fusion

作　　者：甘斌[1] Gan Bin(Xi'an Surveying and Mapping Institute,Xi'an,China)

机构地区：[1]西安市勘察测绘院,陕西西安

出　　处：《科学技术创新》2023年第5期9-14,共6页Scientific and Technological Innovation

摘　　要：针对传统点云压缩算法压缩精度和压缩速度不均衡的问题,提出了一种点云曲度与八叉树结合的点云压缩算法,利用点云曲度能够精确表示点云表面特征的特性和八叉树快速索引的特性,在保证点云压缩精度的同时提高压缩速度,较好地解决了点云压缩精度和速度不均衡问题。采用兔子点云数据进行实验,结果表明:本算法既在保证压缩精度的同时,又能够在一定程度上缩短压缩时间,特别是针对海量点云数据的压缩更能够体现本算法压缩精度和压缩速度的优势。Aiming at the problem that the compression accuracy and compression speed of traditional point cloud compression algorithms are not balanced,a point cloud compression algorithm combining point cloud curvature and octree is proposed.By using the characteristics of point cloud curvature that can accurately represent the surface characteristics of point cloud and the characteristics of octree fast index,the compression speed is improved while ensuring the compression accuracy of point cloud,and the problem of point cloud compression accuracy and speed imbalance is well solved.The experimental results using rabbit point cloud data show that this algorithm can not only ensure the compression accuracy,but also shorten the compression time to a certain extent,especially for the massive point cloud data compression can reflect the advantages of this algorithm compression accuracy and compression speed.

关 键 词：曲度 最优八叉树 点云压缩 压缩精度 压缩速度 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]