Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00211050" target="_blank" >RIV/68407700:21230/13:00211050 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.cescg.org/CESCG-2013/papers/Egert-Efficient_GPU-based_Decompression_of_BTF_Data_Compressed_using_Multi-Level_Vector_Quantization.pdf" target="_blank" >http://www.cescg.org/CESCG-2013/papers/Egert-Efficient_GPU-based_Decompression_of_BTF_Data_Compressed_using_Multi-Level_Vector_Quantization.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization

Popis výsledku v původním jazyce

One of the main drawbacks of Bidirectional Texture Function (BTF), as a method of capturing realistic and accurate real-world material appearance, is the resulting size of the measured data set. Several lossy methods to compress the data were proposed over the years to cope with this problem. To efficiently use the compressed data an appropriate decompression algorithms are also needed, allowing fast random synthesis of BTF data without the need to reconstruct the whole BTF back to its original representation. One of such methods based on multi-level vector quantization and providing both good compression ratio and random access from the compressed data was proposed by Havran et al. in 2010. In this paper, we would like to share our experience with writing a GPU based implementation of the decompression part of the aforementioned method. Our goal was to evaluate the implementation difficulty, as well as the resulting performance and suitability of the algorithm for real-time use.

Název v anglickém jazyce

Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization

Popis výsledku anglicky

One of the main drawbacks of Bidirectional Texture Function (BTF), as a method of capturing realistic and accurate real-world material appearance, is the resulting size of the measured data set. Several lossy methods to compress the data were proposed over the years to cope with this problem. To efficiently use the compressed data an appropriate decompression algorithms are also needed, allowing fast random synthesis of BTF data without the need to reconstruct the whole BTF back to its original representation. One of such methods based on multi-level vector quantization and providing both good compression ratio and random access from the compressed data was proposed by Havran et al. in 2010. In this paper, we would like to share our experience with writing a GPU based implementation of the decompression part of the aforementioned method. Our goal was to evaluate the implementation difficulty, as well as the resulting performance and suitability of the algorithm for real-time use.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

<a href="/cs/project/GAP202%2F12%2F2413" target="_blank" >GAP202/12/2413: Optimální algoritmy pro syntézu obrazu</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 17th Central European Seminar on Computer Graphics

ISBN

978-3-9502533-5-1

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

—

Název nakladatele

Institute of Computer Graphics and Algorithms

Místo vydání

Vienna

Místo konání akce

Smolenice

Datum konání akce

28. 4. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—