Next: Introduction
Thomas Theußl 1
Torsten Möller 2
Meister Eduard Gröller 1
Figure 1:
CT scans of a lobster and a tooth, represented on Cartesian and body-centered
cubic grids (left and right images, respectively). The
representation via body-centered cubic grids requires
approximately 30% less samples.
|
Abstract:
The classification of volumetric data sets as well as their
rendering algorithms are typically based on the representation of
the underlying grid. Grid structures based on a Cartesian lattice
are the de-facto standard for regular representations of volumetric
data. In this paper we introduce a more general concept of regular
grids for the representation of volumetric data. We demonstrate that
a specific type of regular lattice - the so-called
body-centered cubic - is able to represent the same data set
as a Cartesian grid to the same accuracy but with 29.3% fewer
samples. This speeds up traditional volume rendering algorithms by
the same ratio, which we demonstrate by adopting a splatting
implementation for these new lattices. We investigate different
filtering methods required for computing the normals on this
lattice. The lattice representation results also in lossless
compression ratios that are better than previously reported.
Although other regular grid structures achieve the same sample
efficiency, the body-centered cubic is particularly easy to use. The
only assumption necessary is that the underlying volume is isotropic
and band-limited - an assumption that is valid for most practical
data sets.
Key words: volume data, Cartesian grid, close packing, hexagonal sampling, body centered cubic
View the paper in .pdf format (latex2html does not work too well with formulas...)
Next: Introduction
Thomas Theußl
2001-08-05