八叉树索引的三维点云数据压缩算法

An Octree-based mesh simplification algorithms for 3-dimension cloud data

针对现有的三维点云简化算法普遍存在运行效率较低、内存消耗大、处理时间过长等问题,该文利用八叉树索引的速度优势和点云数据空间分割的逻辑结构,并结合三维点云网格简化算法高效的优势,提出一种基于八叉树索引的三维点云简化算法。该算法基本满足点云简化的理想标准,计算快速、运行时间短。利用实测大雁塔数据对各种三维点云压缩算法进行比较,结果表明该文提出的新算法对点云数据的压缩简化效率和压缩率较现有算法均有较大提高。

The large density point cloud data need to be simplified during the 3D laser scanning data processing, but the existing simplification algorithm generally has the disadvantages such as low efficien- cy, large memory consumption, long processing time and other problems. This paper put forward a sim- plification algorithm based on Octree index of 3D point data, which using the advantage of the Oetree in- dexing speed and logical structure of spatial segmentation of point cloud data and combing the advantages of high efficiency by the 3D point cloud mesh simplification algorithm. Comparing this algorithm with other 3D point cloud compression algorithms using the measured data of Dayan Pagoda, the results showed that this algorithm had a great advantage on the compression and simplification of point cloud data; the effi- ciency and compression ratio were