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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F10%3A00057180%21RIV13-GA0-14330___
rdf:type
n6: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/00216224:14330/10:00057180!RIV13-GA0-14330___
n3:aktivita
n17:Z n17:S n17:P
n3:aktivity
P(GD102/09/H042), S, Z(MSM0021622419), Z(MSM6383917201)
n3:dodaniDat
n16:2013
n3:domaciTvurceVysledku
n8:3893995 n8:2121816 n8:6964273
n3:druhVysledku
n7:D
n3:duvernostUdaju
n14:S
n3:entitaPredkladatele
n15:predkladatel
n3:idSjednocenehoVysledku
260918
n3:idVysledku
RIV/00216224:14330/10:00057180
n3:jazykVysledku
n21:eng
n3:klicovaSlova
EBCOT; JPEG2000; Tier-1; GPU; context modeller
n3:klicoveSlovo
n4:context%20modeller n4:Tier-1 n4:JPEG2000 n4:EBCOT n4:GPU
n3:kontrolniKodProRIV
[207D973627B8]
n3:mistoKonaniAkce
Mikulov
n3:mistoVydani
Brno
n3:nazevZdroje
MEMICS 2010 Proceedings
n3:obor
n10:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n5:GD102%2F09%2FH042
n3:rokUplatneniVysledku
n16:2010
n3:tvurceVysledku
Holub, Petr Matela, Jiří Rusňák, Vít
n3:typAkce
n13:EUR
n3:zahajeniAkce
2010-01-01+01:00
n3:zamer
n12:MSM6383917201 n12:MSM0021622419
s:numberOfPages
9
n22:hasPublisher
NOVPRESS
n20:isbn
9788087342107
n19:organizacniJednotka
14330