Representation and extraction of volumetric attributes using trivariate splines: a mathematical framework
Representation and extraction of volumetric attributes using trivariate splines: a mathematical framework
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DOI：
10.1145/376957.376984
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发表时间：
2001-05
期刊：
影响因子：
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通讯作者：
William Martin;E. Cohen
中科院分区：
文献类型：
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作者：
William Martin;E. Cohen
我们在本文中的目标是利用传统的几何设计和科学可视化社区的优势，以产生一个有价值的工具。我们提出了一种方法表示和指定属性数据在一个三变量NURBS体。一些相关属性量包括材料成分和密度、光学折射率和色散以及来自医学成像的数据。该方法独立于物理几何形状的粒度，允许将所携带的数据的分辨率与体积的分辨率解耦。可以对体积属性进行建模或拟合数据。提出了一种三变量NURBS曲线的有效评价方法。我们将数据分析和可视化的方法，包括等值面提取，平面切片，体积射线跟踪，和光路跟踪，所有这些都是接地样条的细化理论。这些技术的应用是多种多样的，包括光学、流体动力学和医学可视化等领域。
Our goal in this paper is to leverage traditional strengths from the geometric design and scientific visualization communities to produce a tool valuable to both. We present a method for representing and specifying attribute data across a trivariate NURBS volume. Some relevant attribute quantities include material composition and density, optical indices of refraction and dispersion, and data from medical imaging. The method is independent of the granularity of the physical geometry, allowing for a decoupling of the resolution of the carried data from that of the volume. Volume attributes can be modeled or fit to data. A method is presented for efficient evaluation of trivariate NURBS. We incorporate methods for data analysis and visualization including isosurface extraction, planar slicing, volume ray tracing, and optical path tracing, all of which are grounded in refinement theory for splines. The applications for these techniques are diverse, including such fields as optics, fluid dynamics, and medical visualization.