Institute for Data Analysis and Visualization

We present a multiresolution technique for interactive texture- based volume visualization of very large data sets. This method uses an adaptive scheme that renders the volume in a region-of- interest at a high resolution and the volume away from this region at progressively lower resolutions. The algorithm is based on the segmentation of texture space into an octree, where the leaves of the tree define the original data and the internal nodes define lower-resolution versions. Rendering is done adaptively by selecting high-resolution cells close to a center of attention and low-resolution cells away from this area. We limit the artifacts introduced by this method by modifying the transfer functions in the lower-resolution data sets and utilizing spherical shells as a proxy geometry. It is possible to use this technique to produce viewpoint-dependent renderings of very large data sets.