Visualization of Irregularly Sampled Volumetric Data

不规则采样体积数据的可视化

• 批准号: 9102497
• 负责人: Jane Wilhelms
• 金额: $ 23.77万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-08-15 至 1995-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9102497&HistoricalAwards=false
• 关键词: Visualization; Irregularly; Sampled; Volumetric; Data

Visualization provides an efficient and powerful means of comprehending complex numeric data. This project investigates approaches to visualization of sampled volumetric data, such as that produced by computational fluid dynamics, tomography, and molecular simulations, particularly those volumes where the samples are irregularly distributed in space. Two common methods for visualization are: 1) to extract features of interest (such as isosurfaces); and 2) to image the while volume as a continuous semi-transparent medium. Most present approaches to visualization are designed for regular rectilinear grids. This project will extend and generalize these approaches to visualization of data in the less regular formats which are found in many applications. The two main approaches will be: 1) to extend existing algorithms to irregular volumes; and 2) to resample the irregular volumes to hierarchical regular volumes. Another aspect of this research is to carefully compare different approaches to certain aspects of visualization, particularly, the "resampling" (interpolation) of 3D data, the mapping from numeric data to visual parameters such as color and transparency, and methods of efficient volume traversal.

可视化提供了一种理解复杂数值数据的有效而强大的手段。该项目研究了采样体积数据的可视化方法，例如由计算流体动力学、断层扫描和分子模拟产生的数据，特别是那些样本在空间中不规则分布的体积。两种常见的可视化方法是：1)提取感兴趣的特征（如等值面）；2)将体积成像为连续的半透明介质。目前大多数可视化方法都是为规则的直线网格设计的。该项目将扩展和推广这些方法，以在许多应用程序中发现的不太规则的格式进行数据可视化。两种主要方法是：1)将现有算法扩展到不规则体；2)将不规则体重新采样为分层规则体。本研究的另一个方面是仔细比较可视化某些方面的不同方法，特别是3D数据的“重采样”（插值），从数字数据到视觉参数（如颜色和透明度）的映射，以及有效的体遍历方法。