Name
Abstract | ||
|---|---|---|
Recent advances in computer graphics have relied on high-quality textures in order to generate photorealistic real-time images. Texture compression standards meet these growing demands for data, but current texture compression schemes use fixed-rate methods where statically sized blocks of pixels are represented using the same numbers of bits irrespective of their data content. In order to account for the natural variation in detail, we present an alternative format that allows variable bit-rate texture compression with minimal changes to texturing hardware. Our proposed scheme uses one additional level of indirection to allow the variation of the block size across the same texture. This single change is exploited to both vary the amount of bits allocated to certain parts of the texture and to duplicate redundant texture information across multiple pixels. To minimize hardware changes, the method picks combinations of block sizes and compression methods from existing fixed-rate standards. With this approach, our method is able to demonstrate energy savings of up to 50%, as well as higher quality compressed textures over current state of the art techniques. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1111/cgf.12842 | Comput. Graph. Forum |
Field | DocType | Volume |
Block size,Computer vision,Texture compression,Computer science,S3 Texture Compression,Texture memory,Artificial intelligence,Pixel,Computer graphics,Texture atlas,Texture filtering | Journal | 35 |
Issue | ISSN | Citations |
2 | 0167-7055 | 2 |
PageRank | References | Authors |
0.39 | 11 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pavel Krajcevski | 1 | 41 | 3.87 |
| Abhinav Golas | 2 | 247 | 9.91 |
| K. Ramani | 3 | 2 | 0.39 |
| M. Shebanow | 4 | 2 | 0.39 |
| Dinesh Manocha | 5 | 9551 | 787.40 |