Representation and extraction of volumetric attributes using trivariate splines
William Martin, Elaine Cohen · 2001
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.