中文摘要：

为实现三维不规则体数据场的高效绘制,提出一种适用于GPU的四面体体数据规则化和可视化算法.将以四面体为基本单元的稀疏体数据用一个有限深度的八叉树结构逼近,并将逼近误差表达为一个离散的完全空间哈希结构;然后将半规则的八叉树转换为规则的八叉树纹理（三维）,并将完全空间哈希表转换为三维查找表,两者均可在绘制时快速随机取值,故可直接作为三维纹理在GPU中访问.通过这种双规则化的表示方法,可将四面体体数据的可视化转化为在GPU中并行地绘制2种三维纹理.实验结果表明,该算法在处理空间稀疏体数据时保证了较高的精度,同时减少了数据存储量.

英文摘要：

To efficiently visualize 3D irregular volumetric datasets,we present a novel approach for GPU-friendly regularization and rendering of tetrahedral volumetric datasets.The key idea is that a sparse tetrahedral volumetric data can be approximated by an octree with a limited depth,and the residual errors can be represented by a hashing table generated by the perfect spatial hashing technique.By converting the octree and the hashing table into an octree texture and a 3D lookup table respectively,a regular and array-wise representation for the underlying dataset is constructed.This dual-regularization reformulation not only allows for random access in GPU,but also makes the visualization of tetrahedral volumetric datasets be identical to rendering two 3D regular textures.Experimental results demonstrate that high quality can be achieved with much less memory consumption than previous approaches when handling sparse datasets.