Detailed Information on Publication Record
2012
GPU-specific reformulations of image compression algorithms
MATELA, Jiří, Petr HOLUB, Martin JIRMAN and Martin ŠROMBasic information
Original name
GPU-specific reformulations of image compression algorithms
Authors
MATELA, Jiří (203 Czech Republic, guarantor, belonging to the institution), Petr HOLUB (203 Czech Republic, belonging to the institution), Martin JIRMAN (203 Czech Republic) and Martin ŠROM (203 Czech Republic)
Edition
8499. vyd. BELLINGHAM, WA 98227-0010 USA, Proceedings of Applications of Digital Image Processing XXXV, p. nestránkováno, 8 pp. 2012
Publisher
SPIE-INT SOC OPTICAL ENGINEERING
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
RIV identification code
RIV/00216224:14330/12:00057518
Organization unit
Faculty of Informatics
ISBN
978-0-8194-9216-6
ISSN
UT WoS
000312200600040
Keywords in English
GPU; parallel; reformulation; JPEG; JPEG2000; Context Modeling; Arithmetic coding; MQ-Coder; Huffman coding
Tags
Tags
International impact, Reviewed
Změněno: 22/4/2013 14:20, doc. RNDr. Petr Holub, Ph.D.
Abstract
V originále
Image compressions have a number of applications in various fields where the processing throughput and/or latency is a crucial attribute and the main limitation with state of the art implementations of compression algorithms. At the same time the contemporary GPUs provide a tremendous processing power applicable to the image compression acceleration but it calls for a specific algorithm design. We discuss the key components of successful GPU algorithm design and demonstrate this on JPEG2000 compression chain, which contains several types of algorithms: from DWT which is inherently well suited to GPU, through context modeling requiring reformulation in order to perform well on GPU, to arithmetic coding which does not fit the paradigm well but can be optimized to perform faster than CPU versions. Performance evaluation of the optimized JPEG2000 chain will be used to demonstrate the importance of various aspects of GPU programming, especially with respect to real-time applications.
Links
GAP202/12/0306, research and development project |
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GD102/09/H042, research and development project |
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MUNI/A/0914/2009, interní kód MU |
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