Extensions to bidirectional texture function compression with multi-level vector quantization in OpenCL

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00233079" target="_blank" >RIV/68407700:21230/15:00233079 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.sciencedirect.com/science/article/pii/S0097849315000060" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0097849315000060</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cag.2015.01.005" target="_blank" >10.1016/j.cag.2015.01.005</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Extensions to bidirectional texture function compression with multi-level vector quantization in OpenCL

Popis výsledku v původním jazyce

Bidirectional 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 three contributions to BTF data compression. First, we propose novel decompositions for multi-level vector quantization in BTF data compression that improve the compression ratio by 12% in comparison with the original method, without loss of visual quality. This is achieved by a highly configurable software architecture that allows for different compression pipelines. Second, we show how for offline storage the compression ratio can be increased by 30% in total by Huffman coding. Third, we show how to efficiently parallelize this vector quantization algorithm in OpenCL for massivelyparallel architectures such as GPUs with a new modular design of the compression pipeline. The results for the new compression algorithm are shown on twelve low dynamic range BTFs and four high dynamic range publicly available BTF samples

Název v anglickém jazyce

Extensions to bidirectional texture function compression with multi-level vector quantization in OpenCL

Popis výsledku anglicky

Bidirectional 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 three contributions to BTF data compression. First, we propose novel decompositions for multi-level vector quantization in BTF data compression that improve the compression ratio by 12% in comparison with the original method, without loss of visual quality. This is achieved by a highly configurable software architecture that allows for different compression pipelines. Second, we show how for offline storage the compression ratio can be increased by 30% in total by Huffman coding. Third, we show how to efficiently parallelize this vector quantization algorithm in OpenCL for massivelyparallel architectures such as GPUs with a new modular design of the compression pipeline. The results for the new compression algorithm are shown on twelve low dynamic range BTFs and four high dynamic range publicly available BTF samples

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computers & Graphics

ISSN

0097-8493

e-ISSN

—

Svazek periodika

48

Číslo periodika v rámci svazku

05

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

1-10

Kód UT WoS článku

000355029200002

EID výsledku v databázi Scopus

2-s2.0-84924787633