Introducing Topological Attributes for Objective-Based Visualization
Y. Takeshima, S. Takahashi, I. Fujishiro, G.M. Nielson · 2005
Direct volume rendering is a standard technique for projecting all the optically-encoded samples onto the screen at once to allow us to peer into the inner structures involved in a volume data. Datacentric approaches to the design of transfer functions (TFs) have recently been well-established, which perform mathematical analysis of the data prior to pertinent rendering. The advent of multidimensional TFs is one of the latest major achievements in the volume visualization research. As opposed to the traditional onedimensional TFs that only consider a voxel’s scalar field value, the multi-dimensional TFs assign auxiliary attributes to the voxels to construct their sophisticated parametric domains. For example, when visualizing volumes obtained by scientific simulations, the observers can utilize their own knowledge about the simulation settings to extract the global characteristics of the volumes and to locate regions of particular interest. If they are allowed to design multi-dimensional TFs using staff attributes so as to encapsulate such advance knowledge, they can readily yield visualization results to fulfill their purposes. Nevertheless, nearly all attributes for the conventional multi-dimensional TFs are based on local features, such as differentials and curvatures, and are difficult to capture the global structure of the volume contrary to the observer’s purposes. This paper therefore introduces a new set of topological attributes to establish a new framework that is intended to realize objective-based assistance. Topological attributes proposed herein are derived from the level-set graph, which delineates the topological evolution of an isosurface with respect to the scalar field.