The Hybrid Octree: Towards the Definition of a Multiresolution Hybrid Framework Imma Boada 1 and Isabel Navazo 2 1 Institut Inform`atica i Aplicacions, Universitat de Girona, Spain imma@ima.udg.es 2 Dep. LSI , Universitat Polit` ecnica de Catalunya, Spain isabel@lsi.upc.es Abstract. The Hybrid Octree (HO) is an octree-based representation scheme for coding in a single model an exact representation of a surface and volume data. The HO is able to efficiently manipulate surface and volume data independently. Moreover, it facilitates the visualization and composition of surface and volume data using graphic hardware. The HO definition and its construction algorithm are provided. Some examples are presented and the goodness of the model is discussed. 1 Introduction The visualization of scenes that integrate surface and volume data in a single image plays an important role in a large number of scientific visualization ap- plications. In surgical planning, for example, the volume information captured from input devices needs to be visualized, manipulated and analyzed along with objects such as osteotomy surfaces, prosthetic devices or scalpels; in meteorology clouds have to be rendered over terrain data, etc,. We define a hybrid scene as an scene composed of surface and volume data. The different techniques that have been proposed to deal with hybrid scenes are based on one of the two following approaches. The data conversion approach that reduces surface and volume data to a common codification scheme, by applying a voxelization process or a polygonalization strategy. Then volume and polygonal data can be rendered using a classical rendering pipeline [5, 6, 15, 18]. The inde- pendent representation approach that preserves original surface and volume data in their independent representation schemes. Data is rendered independently, by the application of two separate rendering processes, and data integration is part of the visualization process which requires the definition of specialized hybrid render algorithms able to composite surface and volume data in depth sorted order. Such an approach usually requires a costly process to properly composite the data [9, 17, 7, 19, 8]. P.M.A. Sloot et al. (Eds.): ICCS 2002, LNCS 2330, pp. 121-130, 2002.  Springer-Verlag Berlin Heidelberg 2002