An Isosurface Continuity Algorithm for Super Adaptive Resolution Data *

Abstract

We present the chain-gang algorithm for isosurfacerendering of super adaptive resolution (SAR) volumedata in order to minimize (1) the space needed for storage of boththe data and the isosurface and (2) the the time taken forcomputation. The chain-gang algorithm is able to resolvediscontinuities in SAR data sets. Unnecessary computation isavoided by skipping over large sets of volume data deemeduninteresting. Memory space is saved by leaving the uninterestingvoxels out of our octree data structure used to traverse the volumedata. Our isosurface generation algorithm extends the MarchingCubes Algorithm in order to handle inconsistencies that can arisebetween abutting cells that are separated by both one and twolevels of resolution.