基于边扩张算法和熵编码的3D网格模型的拓扑信息压缩

Topologic compression for 3D mesh model based on Face Fixer method

本文总结了三类不经三角剖分直接编码多边形网格模型拓扑信息的单分辨率压缩法,对其中基于边区域扩张的Face Fixer算法进行了研究,并分别应用同阶自适应区间编码法和算术编码法对三角形网格模型和多边形网格模型进行了压缩。实验结果表明:随着模型数据量的增大,区间编码的压缩率和压缩速度反而高于算术编码,因而对于大数据量的网格模型,更适宜采用区间编码来压缩。

Firstly, three categorizes methods of compressing polygon mesh topologic information without triangulations were summarized in the paper. Then, the Face Fixer algorithm based on edge conquering was studied. Finally, several 3D mesh models were compressed after topologic encoding when using the same order adaptive arithmetic coder and range coder. The experiments results showed that range coder is superior to arithmetic coder in compression ratio and velocity with the increasing model size. Thus, for larger model, the adaptive range coder is preferred to compress.