| Abstract |
In many applications surfaces containing a large
number of primitives occur. Geometry compression
reduces storage space and transmission time
for such models. A special case is given by polygonal
isosurfaces generated from gridded volume
data. However, most current state-of-the-art geometry
compression systems do not capitalize on the
structure that is characteristic of such isosurfaces,
namely that the surfaces are defined by a set of vertices
on edges of the grid. We propose a compression
method for isosurfaces that is designed to exploit
this feature. We tested our method for several
isosurfaces from a CT scan of a human head. For
this data set our coder outperformed state-of-the-art
geometry compression methods by a factor of 2.2 to
2.8 in terms of compression ratio. |