Per Wennersten

Floating-point buffer compression in a unified codec architecture

This paper presents what we believe are the first (public) algorithms for floating-point (fp) color and fp depth buffer compression. The depth codec is also available in an integer version. The codecs are harmonized, meaning that they share basic technology, making it easier to use the same hardware unit for both types of compression. We further suggest to use these codecs in a unified codec architecture, meaning that compression/decompression units previously only used for color-and depth buffer compression can be used also during texture accesses. Finally, we investigate the bandwidth implication of using this in a unified cache architecture. The proposed fp16 color buffer codec compresses data down to 40% of the original, and the fp16 depth codec allows compression down to 4.5 bpp, compared to 5.3 for the state-of-the-art int24 depth compression method. If used in a unified codec and cache architecture, bandwidth reductions of about 50% are possible, which is significant.

Table-based Alpha Compression

In this paper we investigate low‐bitrate compression of scalar textures such as alpha maps, down to one or two bits per pixel. We present two new techniques for 4 × 4 blocks, based on the idea from ETC to use index tables. We demonstrate that although the visual quality of the alpha maps is greatly reduced at these low bit rates, the quality of the final rendered images appears to be sufficient for a wide range of applications, thus allowing bandwidth savings of up to 75%. The 2 bpp version improves PSNR with over 2 dB compared to BTC at the same bit rate. The 1 bpp version is, to the best of our knowledge, the first public 1 bpp texture compression algorithm, which makes comparison hard. However, compared to just DXT5‐compressing a subsampled texture, our 1 bpp technique improves PSNR with over 2 dB. Finally, we show that some aspects of the presented algorithms are also useful for the more common bit rate of four bits per pixel, achieving PSNR scores around 1 dB better than DXT5, over a set of test images.

Lossless compression of already compressed textures

Texture compression helps rendering by reducing the footprint in graphics memory, thus allowing for more textures, and by lowering the number of memory accesses between the graphics processor and memory, increasing performance and lowering power consumption. Compared to image compression methods like JPEG however, textures codecs are typically much less efficient, which is a problem when downloading the texture over a network or reading it from disk. Therefore, in this paper we investigate lossless compression of already compressed textures. By predicting compression parameters in the image domain instead of in the parameter domain, a more efficient representation is obtained compared to using general compression such as ZIP or LZMA. This works well also for pixel indices that have previously proved hard to compress. A 4-bit-per-pixel format can thus be compressed to around 2.3 bits per pixel (bpp), or 9.6% of the original size, compared to around 3.0 bpp when using ZIP or 2.8 bpp using LZMA. Compressing the original images with JPEG to the same quality also gives 2.3 bpp, meaning that texture compression followed by our packing is on par with JPEG in terms of compression efficiency.