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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F11%3A00049746%21RIV12-GA0-14330___
rdf:type
n8:Vysledek skos:Concept
dcterms:description
Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. EBCOT itself consists of two tiers. In Tier-1, image samples are compressed using context modeling and arithmetic coding. Resulting bit-stream is further formated and truncated in Tier-2. JPEG2000 has a number of applications in various fields where the processing speed and/or latency is a crucial attribute and the main limitation with state of the art implementations. In this paper we propose a new parallel approach to EBCOT context modeling that truly exploits massively parallel capabilities of modern GPUs and enables concurrent processing of individual image samples. Performance evaluation of our prototype shows speedup 12 times for the context modeller, and 1.4--5.3 times for the whole EBCOT Tier-1, which includes not yet optimized arithmetic coder. Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. EBCOT itself consists of two tiers. In Tier-1, image samples are compressed using context modeling and arithmetic coding. Resulting bit-stream is further formated and truncated in Tier-2. JPEG2000 has a number of applications in various fields where the processing speed and/or latency is a crucial attribute and the main limitation with state of the art implementations. In this paper we propose a new parallel approach to EBCOT context modeling that truly exploits massively parallel capabilities of modern GPUs and enables concurrent processing of individual image samples. Performance evaluation of our prototype shows speedup 12 times for the context modeller, and 1.4--5.3 times for the whole EBCOT Tier-1, which includes not yet optimized arithmetic coder.
dcterms:title
GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000 GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000
skos:prefLabel
GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000 GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000
skos:notation
RIV/00216224:14330/11:00049746!RIV12-GA0-14330___
n8:predkladatel
n16:orjk%3A14330
n3:aktivita
n5:Z n5:S n5:P
n3:aktivity
P(GD102/09/H042), S, Z(MSM0021622419)
n3:dodaniDat
n7:2012
n3:domaciTvurceVysledku
n14:3893995 n14:6964273 n14:2121816
n3:druhVysledku
n20:D
n3:duvernostUdaju
n10:S
n3:entitaPredkladatele
n22:predkladatel
n3:idSjednocenehoVysledku
201462
n3:idVysledku
RIV/00216224:14330/11:00049746
n3:jazykVysledku
n18:eng
n3:klicovaSlova
EBCOT; JPEG2000; Tier-1; GPU; context modeller
n3:klicoveSlovo
n6:JPEG2000 n6:GPU n6:context%20modeller n6:EBCOT n6:Tier-1
n3:kontrolniKodProRIV
[1F9EA6A5CA9E]
n3:mistoKonaniAkce
Dagstuhl, Germany
n3:mistoVydani
Dagstuhl, Germany
n3:nazevZdroje
Sixth Doctoral Workshop on Mathematical and Engineering Methods in Computer Science -- Selected Papers
n3:obor
n21:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n17:GD102%2F09%2FH042
n3:rokUplatneniVysledku
n7:2011
n3:tvurceVysledku
Matela, Jiří Holub, Petr Rusňák, Vít
n3:typAkce
n13:CST
n3:zahajeniAkce
2011-01-01+01:00
n3:zamer
n19:MSM0021622419
s:issn
2190-6807
s:numberOfPages
8
n23:hasPublisher
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
n4:isbn
978-3-939897-22-4
n15:organizacniJednotka
14330