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Texture compression

From Wikipedia, the free encyclopedia
Type of data compression
Three-dimensional (3D)
computer graphics
Fundamentals
Primary uses
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Texture compression is a specialized form ofimage compression designed for storingtexture maps in3D computer graphics rendering systems. Unlike conventional image compression algorithms, texture compression algorithms are optimized forrandom access.

Texture compression can be applied to reduce memory usage at runtime. Texture data is often the largest source of memory usage in a mobile application.[citation needed]

Tradeoffs

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In their seminal paper on texture compression,[1] Beers, Agrawala and Chaddha list four features that tend to differentiate texture compression from other image compression techniques. These features are:

Decoding Speed
It is highly desirable to be able to render directly from the compressed texture data and so, in order not to impact rendering performance, decompression must be fast.
Random Access
Since predicting the order that a renderer accessestexels would be difficult, any texture compression scheme must allow fast random access to decompressed texture data. This tends to rule out many better-known image compression schemes such asJPEG orrun-length encoding.
Compression Rate and Visual Quality
In a rendering system, lossy compression can be more tolerable than for other use cases. Some texture compression libraries, such as crunch,[2] allow the developer to flexibly trade off compression rate vs. visual quality, using methods such asrate-distortion optimization (RDO).
Encoding Speed
Texture compression is more tolerant of asymmetric encoding/decoding rates as the encoding process is often done only once during the application authoring process.

Given the above, most texture compression algorithms involve some form of fixed-ratelossyvector quantization of small fixed-size blocks of pixels into small fixed-size blocks of coding bits, sometimes with additional extra pre-processing and post-processing steps.Block Truncation Coding is a very simple example of this family of algorithms.

Because their data access patterns are well-defined, texture decompression may be executed on-the-fly during rendering as part of the overallgraphics pipeline, reducing overall bandwidth and storage needs throughout the graphics system. As well as texture maps, texture compression may also be used to encode other kinds of rendering map, includingbump maps andsurface normal maps. Texture compression may also be used together with other forms of map processing such asMIP maps andanisotropic filtering.

Availability

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Some examples of practical texture compression systems areS3 Texture Compression (S3TC),PVRTC,Ericsson Texture Compression (ETC) andAdaptive Scalable Texture Compression (ASTC); these may be supported by special function units in modernGraphics processing units.

OpenGL and OpenGL ES, as implemented on many video accelerator cards and mobile GPUs, can support multiple common kinds of texture compression - generally through the use of vendor extensions.

Supercompression

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A compressed-texture can be further compressed in what is called "supercompression". Fixed-rate texture compression formats are optimized for random access and are much less efficient compared to image formats such asPNG. By adding further compression, a programmer can reduce the efficiency gap. The extra layer can be decompressed by the CPU so that the GPU receives a normal compressed texture,[3] or in newer methods, decompressed by the GPU itself. Supercompression saves the same amount of VRAM as regular texture compression, but saves more disk space and download size.[4]

Further information:Adaptive scalable texture compression § Universal ASTC, andS3 Texture Compression § Data preconditioning

Neural Texture Compression

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Random-Access Neural Compression of Material Textures (Neural Texture Compression) is aNvidia's technology which enables two additional levels of detail (16x moretexels, so four times higher resolution) while maintaining similar storage requirements as traditional texture compression methods.[5]

The key idea is compressing multiple material textures and theirmipmap chains together, and using a smallneural network, that is optimized for each material, to decompress them.[6]

See also

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References

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  1. ^Andrew Beers; Maneesh Agrawala; Navin Chaddha (1996),"Rendering from Compressed Textures",Computer Graphics, Proc. SIGGRAPH:373–378
  2. ^"crunch open source texture compression library".GitHub. Retrieved2016-09-13.
  3. ^Strom, Jacob; Wennersten, Per (5 August 2011).Lossless compression of already compressed textures. HPG '11: Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics. pp. 177–182.doi:10.1145/2018323.2018351.
  4. ^Krajcevski, Pavel; Pratapa, Srihari; Manocha, Dinesh (11 November 2016)."GST: GPU-decodable supercompressed textures".ACM Transactions on Graphics.35 (6):1–10.doi:10.1145/2980179.2982439.
  5. ^"Nvidia Uses Neural Network for Innovative Texture Compression Method". 6 May 2023.
  6. ^"Random-Access Neural Compression of Material Textures | Research".

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