In this paper, we present a novel out-of-core technique for the interactive computation of isosurfaces from volume data. Our algorithm minimizes the main memory and disk space requirements on the visualization workstation, while speeding up isosurface extraction queries. Our overall approach is a two-level indexing scheme. First, by our meta-cell technique, we partition the original dataset into clusters of cells, called meta-cells. Secondly, we produce metaintervals associated with the meta-cells, and build an indexing data structure on the meta-intervals. We separate the cell information, kept only in meta-cells in disk, from the indexing structure, which is also in disk and only contains pointers to meta-cells. Our meta-cell technique is an I/O-efficient approach for computing a k-d-tree-like partition of the dataset. Our indexing data structure, the binaryblocked I/O interval tree, is a new I/O-optimal data structure to perform stabbing queries that report from a set of meta-inter...
Yi-Jen Chiang, Cláudio T. Silva, William J.