Gaussian transfer functions for multi-field volume visualization
Gaussian transfer functions for multi-field volume visualization
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DOI：
10.1109/visual.2003.1250412
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发表时间：
2003-10
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影响因子：
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通讯作者：
J. Kniss;Simon Premoze;M. Ikits;Aaron E. Lefohn;C. Hansen;Emil Praun
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作者：
J. Kniss;Simon Premoze;M. Ikits;Aaron E. Lefohn;C. Hansen;Emil Praun
体绘制是一种用于可视化密集三维体数据集的灵活技术。体绘制的一个核心元素是数据值和可观测量(如颜色和不透明度)之间的转换。这一过程通常通过使用预先计算并存储在查找表中的传递函数来实现。对于应用于多变量数据的多维传递函数，这些查找表变得大得令人望而却步。我们提出了一种基于高斯和的特殊类型传递函数的直接求值方法。由于它们的形式简单(就参数数量而言)，这些函数及其沿直线段的解析积分可以在当前的图形硬件上有效地计算，从而消除了对预计算查找表的需要。我们采用这些传递函数是因为它们非常适合于基于在传递函数域中定位特征的多个数据值的唯一组合来进行分类。我们将该技术应用于几个多变量数据集(CT、冰冻切片)的可视化，这些数据集很难使用传统方法以交互速度进行准确分类和绘制。
Volume rendering is a flexible technique for visualizing dense 3D volumetric datasets. A central element of volume rendering is the conversion between data values and observable quantities such as color and opacity. This process is usually realized through the use of transfer functions that are precomputed and stored in lookup tables. For multidimensional transfer functions applied to multivariate data, these lookup tables become prohibitively large. We propose the direct evaluation of a particular type of transfer functions based on a sum of Gaussians. Because of their simple form (in terms of number of parameters), these functions and their analytic integrals along line segments can be evaluated efficiently on current graphics hardware, obviating the need for precomputed lookup tables. We have adopted these transfer functions because they are well suited for classification based on a unique combination of multiple data values that localize features in the transfer function domain. We apply this technique to the visualization of several multivariate datasets (CT, cryosection) that are difficult to classify and render accurately at interactive rates using traditional approaches.