Feature preserved volume simplification

Abstract

The goal of this work is to simplify volumetric datasets while preserving the sharp boundary features and the topology of the 3D scalar field. The simplification is performed on the volumetric datasets defined as a tetrahedral mesh. The sharp boundary features are detected and preserved in the simplification to conserve the salient details of the tetrahedral mesh. The topology of the 3D scalar field is preserved by maintaining critical points extracted from the original dataset. No critical vertices are removed or generated during the simplification process. A gradient magnitude based error metric is used to estimate the error associated with a simplification step. The simplified tetrahedral mesh is rendered using a hardware-accelerated unstructured volume rendering algorithm. This method produces results which are visually similar to the original dataset.