A scattered volumetric dataset is regarded as a sampled version of a scalar field defined over a three-dimensional domain, whose graph is a hypersurface embedded in a fourdimensional space. We propose a multiresolution model for the representation and visualization of such dataset, based on a decomposition of the three-dimensional 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.
Multiresolution modeling and visualization of volume data based on simplicial complexes
De Floriani L.;Puppo E.;
1994-01-01
Abstract
A scattered volumetric dataset is regarded as a sampled version of a scalar field defined over a three-dimensional domain, whose graph is a hypersurface embedded in a fourdimensional space. We propose a multiresolution model for the representation and visualization of such dataset, based on a decomposition of the three-dimensional 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.
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