Multiresolution Data Handling for Visualization of Very Large Data Sets

Abstract

We discuss some features of an experimental system for visualization of large (medical) volume data sets. Input voxel data sets are subdivided into blocks first. Then each block is decomposed into a multiresolution data representation by applying a reversible 3D integer Haar wavelet transform (S-transform). The resulting transform coefficients are encoded using a Golomb-Rice algorithm. For volume visualization, we selectively load and decompress blocks to a proper resolution. Then they are rendered into a common view. From our experiments, we learned that large volume data sets should preferably be stored using a multiresolution data representation. Depending on the size of the volume data set and the rendering mode, we also found that a block-based data representation can provide some advantages, but it may not always be the best choice.