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基于数据类型转换的点云快速有损压缩算法

  

  • 出版日期:2016-04-28 发布日期:2016-05-20

A Fast and Lossy Compression Algorithm for Point-Cloud Models Based on#br# Data Type Conversion

  • Online:2016-04-28 Published:2016-05-20

摘要: 针对海量三维点云数据为计算机存储和传输增加沉重负担的问题,提出一种基于数
据类型转换的点云快速有损压缩算法。首先设计出一种数据类型转化规则-FtoI 规则,根据FtoI
规则将浮点数类型点云转换成整数类型点云,然后将整数类型点云切分成许多小单元面块,每一
单元点云生成最小生成树,按广度优先的顺序对树形结构进行编码。同时,按照树形结构对父子
节点的差值进行编码,把整型差值分成两部分编码,符号一部分,其绝对值一部分,其中绝对值
部分采用算术编码进行压缩。实验表明该文算法在保证整个三维点云模型的质量情况下,具有不
错的压缩速度和压缩率。

关键词: 三维点云, 有损压缩, 浮点数, 最小生成树, 算术编码

Abstract: In order to solve computer storage and transmission problem due to massive 3D point cloud,
a fast and lossy compression algorithm for point-cloud models based on data type conversion is
proposed. Firstly, a data type conversion rule-FtoI rule is designed. According to the FtoI rule,
float-point type point cloud is converted to integer type point cloud, then the integer type point-based
surface is split into many sized surface patches, the points of every patches construct a minimum
spanning tree, which is encoded in breadth first order. Besides we encode the difference between father
node and son node according to the minimum spanning tree, the difference is split into two parts, one is
sign, another is absolute value, which is encoded by arithmetic coding. Experiments show that this
compression algorithm has a nice compression speed and compression ratio without losing the quality
of point-cloud model.

Key words: 3D point cloud, lossy compression, float, the minimum spanning tree, arithmetic coding