Merged Multiresolution Hierarchies for Shadow Map Compression

Multiresolution Hierarchies (MH) and Directed Acyclic Graphs (DAG) are two recent approaches for the compression of high-resolution shadow information. In this paper, we introduce Merged Multiresolution Hierarchies (MMH), a novel data structure that unifies both concepts. An MMH leverages both hierarchical homogeneity exploited in MHs, as well as topological similarities exploited in DAG representations. We propose an efficient hash-based technique to quickly identify and remove redundant subtree instances in a modified relative MH representation. Our solution remains lossless and significantly improves the compression rate compared to both preceding shadow map compression algorithms, while retaining the full run-time performance of traditional MH representations.