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dc.contributor.authorAndujar, Carlosen_US
dc.contributor.authorMartinez, Jonasen_US
dc.contributor.editorCarlos Andujar and Javier Lluchen_US
dc.description.abstractCurrent schemes for texture compression fail to exploit spatial coherence in an adaptive manner due to the strict efficiency constraints imposed by GPU-based, fragment-level decompression. In this paper we present a texture compression framework for quasi-lossless, locally-adaptive compression of graphics data. Key elements include a Hilbert scan to maximize spatial coherence, efficient encoding of homogeneous image regions through arbitrarilysized texel runs, a cumulative run-length encoding supporting fast random-access, and a compression algorithm suitable for fixed-rate and variable-rate encoding. Our scheme can be easily integrated into the rasterization pipeline of current programmable graphics hardware allowing real-time GPU decompression. We show that our scheme clearly outperforms competing approaches such as S3TC DXT1 on a large class of images with some degree of spatial coherence. Unlike other proprietary formats, our scheme is suitable for compression of any graphics data including color maps, shadow maps and relief maps. We have observed compression rates of up to 12:1, with minimal or no loss in visual quality and a small impact on rendering time.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: 3D Graphics and Realism - Textureen_US
dc.titleLocally-Adaptive Texture Compressionen_US
dc.description.seriesinformationCEIG 09 - Congreso Espanol de Informatica Graficaen_US

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  • CEIG09
    ISBN 978-3-905673-72-2

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