增量几何压缩

提出了一个几何压缩算法,用以节省三角网格模型存储和传输时间.它首先递归地以区域扩张方式将模型分解为一系列的层结构,利用层间的连贯性以及对层结构的有效编码,实现了高效的拓扑压缩.同时,还设计了一个有效的非线性预测器来实现几何位置的压缩.与以前的算法相比,它具有线性复杂度、压缩比高、执行速度快的特点.实验结果表明,存储一个三角形的拓扑信息平均只需1.42比特.

Incremental Geometric Compression

A geometric compression algorithm is presented in this paper to save the geometry model storage and transmission time. This method decomposes the model into a series of layers in a way of region growing. These layers are then encoded effectively by using inter-layers coherence, so that the topology information of the model is compressed dramatically. Experimental results show that it takes only an average of 1.42 bits per triangle. Additionally, a non-linear geometry predictor is designed to compress the geometric information. Compared with the previous work, this algorithm is of linear complexity, and it can be implemented effectively.