Name
Abstract | ||
|---|---|---|
The quality of shadow mapping is traditionally limited by texture resolution. We present a novel lossless compression scheme for high-resolution shadow maps based on precomputed multiresolution hierarchies. Traditional multiresolution trees can compactly represent homogeneous regions of shadow maps at coarser levels, but require many nodes for fine details. By conservatively adapting the depth map, we can significantly reduce the tree complexity. Our proposed method offers high compression rates, avoids quantization errors, exploits coherency along all data dimensions, and is well-suited for GPU architectures. Our approach can be applied for coherent shadow maps as well, enabling several applications, including high-quality soft shadows and dynamic lights moving on fixed-trajectories. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1111/cgf.12835 | Comput. Graph. Forum |
Field | DocType | Volume |
Computer vision,Texture compression,Computer science,S3 Texture Compression,Shadow mapping,Theoretical computer science,Artificial intelligence,Real-time computer graphics,Depth map,Quantization (signal processing),Computer graphics,Lossless compression | Journal | 35 |
Issue | ISSN | Citations |
2 | 0167-7055 | 3 |
PageRank | References | Authors |
0.40 | 16 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonardo Scandolo | 1 | 12 | 4.71 |
| Pablo Bauszat | 2 | 77 | 8.25 |
| Elmar Eisemann | 3 | 35 | 6.55 |