Parallel BTF Compression with Multi-Level Vector Quantization in OpenCL

dc.contributor.authorEgert, Petren_US
dc.contributor.authorVlastimil, Havranen_US
dc.contributor.editorJohn Keyser and Young J. Kim and Peter Wonkaen_US
dc.date.accessioned2014-12-16T07:23:39Z
dc.date.available2014-12-16T07:23:39Z
dc.date.issued2014en_US
dc.description.abstractBidirectional Texture Function (BTF) as an effective visual fidelity representation of surface appearance is becoming more and more widely used. In this paper we report on contributions to BTF data compression for multi-level vector quantization. We describe novel decompositions that improve the compression ratio by 15% in comparison with the original method, without loss of visual quality. Further, we show how for offline storage the compression ratio can be increased by 33% in total by Huffman coding. We also show that efficient parallelization of the vector quantization algorithm in OpenCL can reduce the compression time by factor of 9 on a GPU. The results for the new compression algorithm are shown on six low dynamic range BTFs and four high dynamic range publicly available BTF samples. Our method allows for real time synthesis on a GPU.en_US
dc.description.seriesinformationPacific Graphics Short Papersen_US
dc.identifier.isbn978-3-905674-73-6en_US
dc.identifier.urihttps://doi.org/10.2312/pgs.20141265en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectShadingen_US
dc.subjecttextureen_US
dc.subjectI.4.1 [Image Processing and Computer Vision]en_US
dc.subjectDigitization and Image Captureen_US
dc.subjectQuantizationen_US
dc.subjectReflectanceen_US
dc.titleParallel BTF Compression with Multi-Level Vector Quantization in OpenCLen_US
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