Practical HDR Texture Compression
| dc.contributor.author | Munkberg, J. | en_US |
| dc.contributor.author | Clarberg, P. | en_US |
| dc.contributor.author | Hasselgren, J. | en_US |
| dc.contributor.author | Akenine-Moeller, T. | en_US |
| dc.date.accessioned | 2015-02-21T13:15:37Z | |
| dc.date.available | 2015-02-21T13:15:37Z | |
| dc.date.issued | 2008 | en_US |
| dc.description.abstract | The use of high dynamic range (HDR) textures in real-time graphics applications can increase realism and provide a more vivid experience. However, the increased bandwidth and storage requirements for uncompressed HDR data can become a major bottleneck. Hence, several recent algorithms for HDR texture compression have been proposed. In this paper, we discuss several practical issues one has to confront in order to develop and implement HDR texture compression schemes. These include improved texture filtering and efficient offline compression. For compression, we describe how Procrustes analysis can be used to quickly match a predefined template shape against chrominance data. To reduce the cost of HDR texture filtering, we perform filtering prior to the colour transformation, and use a simple trick to reduce the incurred errors. We also introduce a number of novel compression modes, which can be combined with existing compression schemes, or used on their own. | en_US |
| dc.description.number | 6 | en_US |
| dc.description.seriesinformation | Computer Graphics Forum | en_US |
| dc.description.volume | 27 | en_US |
| dc.identifier.doi | 10.1111/j.1467-8659.2008.01174.x | en_US |
| dc.identifier.issn | 1467-8659 | en_US |
| dc.identifier.pages | 1664-1676 | en_US |
| dc.identifier.uri | https://doi.org/10.1111/j.1467-8659.2008.01174.x | en_US |
| dc.publisher | The Eurographics Association and Blackwell Publishing Ltd | en_US |
| dc.title | Practical HDR Texture Compression | en_US |