State-Based Multi-parameter Probability Estimation for Context-Based Adaptive Binary Arithmetic Coding

In this paper we present a "State-Based Multi-Parameter Probability Estimation" (SBMP) for Context-Based Adaptive Binary Arithmetic Coding (CABAC) which employs a two hypotheses probability estimator based on exponentially weighted moving averages. It uses a logarithmic state representatio...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:DCC (Los Alamitos, Calif.) s. 163 - 172
Hlavní autori: Haase, Paul, Matlage, Stefan, Kirchhoffer, Heiner, Bartnik, Christian, Schwarz, Heiko, Marpe, Detlev, Wiegand, Thomas
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.03.2020
Predmet:
ISSN:2375-0359
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract In this paper we present a "State-Based Multi-Parameter Probability Estimation" (SBMP) for Context-Based Adaptive Binary Arithmetic Coding (CABAC) which employs a two hypotheses probability estimator based on exponentially weighted moving averages. It uses a logarithmic state representation and a single subsampled transition table with only 32 elements for the probability update. This reduces the memory requirements virtually without affecting the compression efficiency, compared to corresponding approaches that use a linear state representation and a computation-based probability update. The proposed scheme is based on simple operations like table look-ups and additions. Compared to the state-of-the-art probability estimator of the video compression standard H.265/HEVC, the compression efficiency is increased by up to 1 % Bjøntegaard-Delta bit rate (BD rate) when applied to draft 2 of the Versatile Video Coding (VVC) standard. Furthermore, SBMP was recently adopted to working draft 2 of the MPEG-7 part 17 standard for compression of neural networks for multimedia content description and analysis.
AbstractList In this paper we present a "State-Based Multi-Parameter Probability Estimation" (SBMP) for Context-Based Adaptive Binary Arithmetic Coding (CABAC) which employs a two hypotheses probability estimator based on exponentially weighted moving averages. It uses a logarithmic state representation and a single subsampled transition table with only 32 elements for the probability update. This reduces the memory requirements virtually without affecting the compression efficiency, compared to corresponding approaches that use a linear state representation and a computation-based probability update. The proposed scheme is based on simple operations like table look-ups and additions. Compared to the state-of-the-art probability estimator of the video compression standard H.265/HEVC, the compression efficiency is increased by up to 1 % Bjøntegaard-Delta bit rate (BD rate) when applied to draft 2 of the Versatile Video Coding (VVC) standard. Furthermore, SBMP was recently adopted to working draft 2 of the MPEG-7 part 17 standard for compression of neural networks for multimedia content description and analysis.
Author Bartnik, Christian
Haase, Paul
Matlage, Stefan
Marpe, Detlev
Schwarz, Heiko
Kirchhoffer, Heiner
Wiegand, Thomas
Author_xml – sequence: 1
  givenname: Paul
  surname: Haase
  fullname: Haase, Paul
  organization: Fraunhofer Heinrich-Hertz-Institute (HHI), Germany
– sequence: 2
  givenname: Stefan
  surname: Matlage
  fullname: Matlage, Stefan
  organization: Fraunhofer Heinrich-Hertz-Institute (HHI), Germany
– sequence: 3
  givenname: Heiner
  surname: Kirchhoffer
  fullname: Kirchhoffer, Heiner
  organization: Fraunhofer Heinrich-Hertz-Institute (HHI), Germany
– sequence: 4
  givenname: Christian
  surname: Bartnik
  fullname: Bartnik, Christian
  organization: Fraunhofer Heinrich-Hertz-Institute (HHI), Germany
– sequence: 5
  givenname: Heiko
  surname: Schwarz
  fullname: Schwarz, Heiko
  organization: Fraunhofer Heinrich-Hertz-Institute (HHI), Germany
– sequence: 6
  givenname: Detlev
  surname: Marpe
  fullname: Marpe, Detlev
  organization: Fraunhofer Heinrich-Hertz-Institute (HHI), Germany
– sequence: 7
  givenname: Thomas
  surname: Wiegand
  fullname: Wiegand, Thomas
  organization: Fraunhofer Heinrich-Hertz-Institute (HHI), Germany
BookMark eNotjstOwzAQRQ0Cibb0C7rJDySMPUkcL9tQHlIRSMC6mtgTMGqTyjGI_j2R6Opuzj06U3HR9R0LsZCQSQnm5rauc425yhQoyABA5WdibnQltapkmRdanouJQl2kgIW5EtNh-BopgFJORPsaKXK6ooFd8vS9iz49UKA9Rw7JS-gbavzOx2OyHqLfU_R9l7R9SOq-i_wbT8elo0P0P5ysfEfhmCyDj5-jw9sRdL77uBaXLe0Gnp92Jt7v1m_1Q7p5vn-sl5vUK8CYajSkDavSSusMM1myrpEIRrYEJAkrRFdgi84WGqG1FvKqMA1SWyIDzsTi3-uZeXsIY3I4bo2EoiwN_gFPqloR
CODEN IEEPAD
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/DCC47342.2020.00024
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISBN 9781728164571
1728164575
EISSN 2375-0359
EndPage 172
ExternalDocumentID 9105669
Genre orig-research
GroupedDBID -~X
29F
6IE
6IF
6IH
6IK
6IL
6IN
AAJGR
AAWTH
ABLEC
ADZIZ
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IEGSK
IPLJI
M43
OCL
RIE
RIL
RNS
ID FETCH-LOGICAL-i203t-739a79e26c1cd9eeacacdb13091fa0a1a3833d53f3dc5730fcc04859b3af63e03
IEDL.DBID RIE
ISICitedReferencesCount 7
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000591183800017&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Jul 30 06:13:05 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i203t-739a79e26c1cd9eeacacdb13091fa0a1a3833d53f3dc5730fcc04859b3af63e03
PageCount 10
ParticipantIDs ieee_primary_9105669
PublicationCentury 2000
PublicationDate 2020-Mar
PublicationDateYYYYMMDD 2020-03-01
PublicationDate_xml – month: 03
  year: 2020
  text: 2020-Mar
PublicationDecade 2020
PublicationTitle DCC (Los Alamitos, Calif.)
PublicationTitleAbbrev DCC
PublicationYear 2020
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0020061
Score 1.7802836
Snippet In this paper we present a "State-Based Multi-Parameter Probability Estimation" (SBMP) for Context-Based Adaptive Binary Arithmetic Coding (CABAC) which...
SourceID ieee
SourceType Publisher
StartPage 163
SubjectTerms Arithmetic
Encoding
Estimation
Memory management
Probability
Table lookup
Transform coding
Video coding
Video compression
Title State-Based Multi-parameter Probability Estimation for Context-Based Adaptive Binary Arithmetic Coding
URI https://ieeexplore.ieee.org/document/9105669
WOSCitedRecordID wos000591183800017&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NTwIxEG2AePCECsbv9ODRyi7dbrdHQIgnwkETbmRoZyIHPoJg4r-37a7owYu3zWa_0mb6Zrbz3mPs3qHSRKCEVQWKTCMIMDmKVDmtgCAvJEWzCT0eF9OpmdTYw4ELg4ix-Qwfw2Hcy3druw-_yjom2MTnps7qWuclV-tQXAUsrlSF0sR0ngaDTMssUK26oXkrCZT2X_4pET5Gzf-9-IS1f3h4fHJAmFNWw9UZa34bMfAqLluMYsoo-h6RHI-UWhEkvZeh1SU8YF6KcX_yoQ_okqvIfbLKozSVr3zLG3sONmHx4_3I0eW97WL3tgwkR39h-IA2ex0NXwbPojJQEItuIndCSwPaYDe3qXUG_RoL1s09apmUIIEUfHkqnZIknVU-1MlaH9DKzCVQLjGR56yxWq_wgvGk0AVIMgX5fIDSDDRQglqlZB35suiStcKwzTalRsasGrGrv09fs-MwL2Uv1w1r7LZ7vGVH9mO3eN_exYn9Ajn8p2Q
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3LTgIxFL1BNNEVKhjfduHSamc6nU6XgBCMSFhgwo6UPiILHsHBxL-37Yzowo27yWReaXN77p3ecw7ArTaMWysZViwzOOFGYilSgyOmOZNWphm1wWyCDwbZeCyGFbjbcmGMMaH5zNz7w7CXr5dq43-VPQhvE5-KHdhlSRKTgq21La88Gpe6QhERD4_tdsJp4slWsW_fIp7U_stBJQBIt_a_Vx9C44eJh4ZbjDmCilkcQ-3bigGVkVkHG5JG3HKYpFEg1WIv6j33zS7-AdNCjvsTdVxIF2xF5NJVFMSpXO1b3NjUcuWXP9QKLF3UXM_yt7mnOboL_Qc04LXbGbV7uLRQwLOY0BxzKiQXJk5VpLQwbpWVSk8dbonISiIj6QpUqhm1VCvmgt0q5UKaiSmVNqWG0BOoLpYLcwqIZDyT1IrMuozARonk0hLDWWSVtq4wOoO6H7bJqlDJmJQjdv736RvY741e-pP-0-D5Ag78HBWdXZdQzdcbcwV76iOfva-vwyR_ARs4qqs
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=DCC+%28Los+Alamitos%2C+Calif.%29&rft.atitle=State-Based+Multi-parameter+Probability+Estimation+for+Context-Based+Adaptive+Binary+Arithmetic+Coding&rft.au=Haase%2C+Paul&rft.au=Matlage%2C+Stefan&rft.au=Kirchhoffer%2C+Heiner&rft.au=Bartnik%2C+Christian&rft.date=2020-03-01&rft.pub=IEEE&rft.eissn=2375-0359&rft.spage=163&rft.epage=172&rft_id=info:doi/10.1109%2FDCC47342.2020.00024&rft.externalDocID=9105669