Progressive Volume Models for Rectilinear Data using Tetrahedral Coons Volumes

We present a new technique for modeling rectilinear volume data. The algorithm produces a trivariate model, F (x; y; z), which is piecewise de ned over tetrahedra that ts the volume data to within a user speci ed tolerance. The technique is adaptive leading to an e cient model that is more complex where the data demands it. The novelty of the present technique is that a valid tetrahedrization is not required. Tetrahedral cells are subdivided as required by the error condition only. This type of cellular decomposition leads to a continuous model by the use of a tetrahedral Coons volume which has the ability to interpolate to arbitrary boundary data.