Double bit range estimation with eight estimators for CABAC in VVC

Abstract This work describes the modification of Context‐based Adaptive Binary Arithmetic Coding (CABAC) using the double bit range estimation in the VVC engine and the consideration of range updates by using eight hypothetical probability estimators. The focus is on the selected adaptation rates pe...

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Main Authors: Ka‐Hou Chan, Sio‐Kei Im
Format: Article
Language:English
Published: Wiley 2022-10-01
Series:IET Image Processing
Online Access:https://doi.org/10.1049/ipr2.12547
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author Ka‐Hou Chan
Sio‐Kei Im
author_facet Ka‐Hou Chan
Sio‐Kei Im
author_sort Ka‐Hou Chan
collection DOAJ
description Abstract This work describes the modification of Context‐based Adaptive Binary Arithmetic Coding (CABAC) using the double bit range estimation in the VVC engine and the consideration of range updates by using eight hypothetical probability estimators. The focus is on the selected adaptation rates performed in these proposed estimators, which are chosen based on memory consideration and coding efficiency. An investigation of arithmetic coding engines with multi‐hypothesis probability estimates and their consideration of contextual modeling of entropy coding at the level of transform coefficients. The proposed scheme enables a quantitative representation of probabilistic predictions linearly and describes the scalability potential for higher accuracy. In addition, this work discusses the hardware implementation, which is based on simple operations such as bitwise operations and subinterval updates. The experimental results validate the effectiveness of the proposed approach specified in VTM framework. The improved results show that it provides more significant gains in terms of RA and LD, which is better than the AI configuration.
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spelling doaj.art-01fe16cc4a3349b7941d2f1fba8aea6f2022-12-22T04:21:48ZengWileyIET Image Processing1751-96591751-96672022-10-0116123155316310.1049/ipr2.12547Double bit range estimation with eight estimators for CABAC in VVCKa‐Hou Chan0Sio‐Kei Im1Faculty of Applied Sciences Macao Polytechnic University Macau ChinaMacao Polytechnic University Macau ChinaAbstract This work describes the modification of Context‐based Adaptive Binary Arithmetic Coding (CABAC) using the double bit range estimation in the VVC engine and the consideration of range updates by using eight hypothetical probability estimators. The focus is on the selected adaptation rates performed in these proposed estimators, which are chosen based on memory consideration and coding efficiency. An investigation of arithmetic coding engines with multi‐hypothesis probability estimates and their consideration of contextual modeling of entropy coding at the level of transform coefficients. The proposed scheme enables a quantitative representation of probabilistic predictions linearly and describes the scalability potential for higher accuracy. In addition, this work discusses the hardware implementation, which is based on simple operations such as bitwise operations and subinterval updates. The experimental results validate the effectiveness of the proposed approach specified in VTM framework. The improved results show that it provides more significant gains in terms of RA and LD, which is better than the AI configuration.https://doi.org/10.1049/ipr2.12547
spellingShingle Ka‐Hou Chan
Sio‐Kei Im
Double bit range estimation with eight estimators for CABAC in VVC
IET Image Processing
title Double bit range estimation with eight estimators for CABAC in VVC
title_full Double bit range estimation with eight estimators for CABAC in VVC
title_fullStr Double bit range estimation with eight estimators for CABAC in VVC
title_full_unstemmed Double bit range estimation with eight estimators for CABAC in VVC
title_short Double bit range estimation with eight estimators for CABAC in VVC
title_sort double bit range estimation with eight estimators for cabac in vvc
url https://doi.org/10.1049/ipr2.12547
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