Multiresolution modeling and visualization of volume data based on simplicial complexes

A scattered volumetric dataset is regarded as a sampled version of a scalar field defined ona three dimensional domain, whose graph is a hypersurface embedded in a four dimensional space. We propose a multiresolution model for the representation and visualization of such data that is based on a decomposition of the threeedimensional domain into tetrahedra. Multiresolution is achieved through a sequence of tetrahedralizations that approximate the scalar field at increasing precision. The construction of the model is based on an adaptive incremental approach driven by the local coherence of the scalar field. The proposed model allows an efficient extraction of compact isosurfaces with adaptive resolution levels, as well as the development of progressive and multiresolution rendering approaches. Experimental evaluations of the proposed approach on different scattered datasets are reported.