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首页> 外文会议>International Conference on Imaging Science, Systems, and Technology CISST'2001 Vol.1, Jun 25-28, 2001, Las Vegas, Nevada, USA >An Octree-based Multiresolution Approach Supporting Interactive Rendering of Very Large Volume Data Sets
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An Octree-based Multiresolution Approach Supporting Interactive Rendering of Very Large Volume Data Sets

机译：基于八进制的多分辨率方法，支持超大量数据集的交互式呈现

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摘要

We present an octree-based approach supporting multiresolution volume rendering of large data sets. Given a set of scattered points without connectivity information, we impose an octree data structure of low resolution in the preprocessing step. The construction of this initial octree structure is controlled by the original data resolution and cell-specific error values. Using the octree nodes, rather than the data points, as elementary units for ray casting, we first generate a crude rendering of a given data set. Keeping the pre-processing step independent from the rendering step, we allow a user to interactively explore a large data set by specifying a region of interest (ROI), where a higher level of rendering accuracy is desired. To refine an ROI, we are making use of the octree constructed in the pre-processing step. Our approach is aimed at minimizing the number of computations and can be applied to large-scale data exploration tasks.
机译：我们提出一种基于八叉树的方法，支持对大型数据集的多分辨率体积渲染。给定一组没有连接信息的分散点，我们在预处理步骤中施加了低分辨率的八叉树数据结构。此初始八叉树结构的构造由原始数据分辨率和特定于单元的错误值控制。使用八叉树节点而不是数据点作为射线投射的基本单位，我们首先生成给定数据集的粗略渲染。保持预处理步骤与渲染步骤无关，我们允许用户通过指定需要更高渲染精度级别的感兴趣区域（ROI）来交互式地浏览大型数据集。为了改善投资回报率，我们利用了预处理步骤中构建的八叉树。我们的方法旨在最大程度地减少计算量，并且可以应用于大规模数据探索任务。

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