Decreasing isosurface complexity via discrete fitting

Since the introduction of techniques for isosurface extraction from volumetric datasets, one of the hardest problems has been to reduce the number of generated triangles (or polygons). This paper presents an algorithm that considerably reduces the number of triangles generated by a Marching Cubes algorithm, while presenting very close or shorter running times. The algorithm first assumes discretization of the dataset space and replaces cell edge interpolation by midpoint selection. Under these assumptions the extracted surfaces are composed of polygons lying within a finite number of incidences, thus allowing simple merging of the output facets into large coplanar triangular facets. Lastly, the vertices which survived the decimation process are located on their exact positions and normals are computed. An experimental evaluation of the proposed approach on datasets relevant to biomedical imaging and chemical modeling is reported.