Higher precision range estimation for context-based adaptive binary arithmetic coding

The Lagrangian rate distortion optimisation is widely employed in modern video encoders, such as high-efficiency video coding (H.265/HEVC). In this work, the authors propose a more accurate context-based adaptive binary arithmetic coding look-up table that can enhance compression quality and provide...

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Veröffentlicht in:IET image processing Jg. 14; H. 1; S. 125 - 131
Hauptverfasser: Im, Sio-Kei, Chan, Ka-Hou
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 10.01.2020
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Abstract The Lagrangian rate distortion optimisation is widely employed in modern video encoders, such as high-efficiency video coding (H.265/HEVC). In this work, the authors propose a more accurate context-based adaptive binary arithmetic coding look-up table that can enhance compression quality and provide substantially better accuracy of range estimation, by employing one-more bit with 64 probability states. For the hardware implementation, they propose a higher precision look-up table instead of the HEVC Test Model (HM) standard table. The authors also define a new finite-state machine to handle the probability changing in real-time. The significant BD-RATE gain of the proposed context modelling is up to 6.0% for all-intra mode and 13.0% for inter mode. This finite state machine offers no divergence from the H.265/HEVC standards and can be used in the current systems.
AbstractList The Lagrangian rate distortion optimisation is widely employed in modern video encoders, such as high-efficiency video coding (H.265/HEVC). In this work, the authors propose a more accurate context-based adaptive binary arithmetic coding look-up table that can enhance compression quality and provide substantially better accuracy of range estimation, by employing one-more bit with 64 probability states. For the hardware implementation, they propose a higher precision look-up table instead of the HEVC Test Model (HM) standard table. The authors also define a new finite-state machine to handle the probability changing in real-time. The significant BD-RATE gain of the proposed context modelling is up to 6.0% for all-intra mode and 13.0% for inter mode. This finite state machine offers no divergence from the H.265/HEVC standards and can be used in the current systems.
Author Chan, Ka-Hou
Im, Sio-Kei
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Cites_doi 10.1109/TCSVT.2003.815168
10.1109/TCSVT.2012.2221191
10.1109/TMM.2014.2307553
10.1109/ICIP.2003.1246667
10.1109/ISCE.2006.1689517
10.1109/TCSVT.2012.2223013
10.1109/ICASSP.2011.5946787
10.1109/JSTSP.2013.2269272
10.1109/PCS.2010.5702513
10.1109/TCSVT.2012.2221255
10.1109/TCSVT.2003.815165
10.1109/TVCG.2006.143
10.1007/978-3-642-22875-9_54
10.1109/79.733497
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Issue 1
Keywords binary codes
finite-state machine
probability
probability states
range estimation
video coding
finite state machines
adaptive codes
arithmetic codes
rate distortion theory
Lagrangian rate distortion optimisation
optimisation
high-efficiency video coding
modern video encoders
HEVC Test Model standard table
accurate context-based adaptive binary arithmetic coding look-up table
context modelling
BD-RATE gain
Language English
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Snippet The Lagrangian rate distortion optimisation is widely employed in modern video encoders, such as high-efficiency video coding (H.265/HEVC). In this work, the...
The Lagrangian rate distortion optimisation is widely employed in modern video encoders, such as high‐efficiency video coding (H.265/HEVC). In this work, the...
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SubjectTerms accurate context‐based adaptive binary arithmetic coding look‐up table
adaptive codes
arithmetic codes
BD‐RATE gain
binary codes
context modelling
finite state machines
finite‐state machine
HEVC Test Model standard table
high‐efficiency video coding
Lagrangian rate distortion optimisation
modern video encoders
optimisation
probability
probability states
range estimation
rate distortion theory
Research Article
video coding
Title Higher precision range estimation for context-based adaptive binary arithmetic coding
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