Details
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (electronic) | 9798350359855 |
| ISBN (print) | 979-8-3503-5986-2 |
| Publication status | Published - 2023 |
| Event | 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 - Jeju, Korea, Republic of Duration: 4 Dec 2023 → 7 Dec 2023 |
Abstract
A Python wrapper for Context-based Adaptive Binary Arithmetic Coding (CABAC), extracted from the Test Model (VTM) for Versatile Video Coding (VVC), is presented. Besides providing Python access to CABAC, two extensions are proposed: The probability estimation progress for each context can be traced, and sequences of integer values can be coded without designing a dedicated context model set.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Hardware and Architecture
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Media Technology
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2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023. Institute of Electrical and Electronics Engineers Inc., 2023.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Python Wrapper for Context-based Adaptive Binary Arithmetic Coding
AU - Rohlfing, Christian
AU - Meyer, Thibaut
AU - Schneider, Jens
AU - Voges, Jan
N1 - Publisher Copyright: © 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - A Python wrapper for Context-based Adaptive Binary Arithmetic Coding (CABAC), extracted from the Test Model (VTM) for Versatile Video Coding (VVC), is presented. Besides providing Python access to CABAC, two extensions are proposed: The probability estimation progress for each context can be traced, and sequences of integer values can be coded without designing a dedicated context model set.
AB - A Python wrapper for Context-based Adaptive Binary Arithmetic Coding (CABAC), extracted from the Test Model (VTM) for Versatile Video Coding (VVC), is presented. Besides providing Python access to CABAC, two extensions are proposed: The probability estimation progress for each context can be traced, and sequences of integer values can be coded without designing a dedicated context model set.
UR - http://www.scopus.com/inward/record.url?scp=85184855408&partnerID=8YFLogxK
U2 - 10.1109/VCIP59821.2023.10402639
DO - 10.1109/VCIP59821.2023.10402639
M3 - Conference contribution
AN - SCOPUS:85184855408
SN - 979-8-3503-5986-2
BT - 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
Y2 - 4 December 2023 through 7 December 2023
ER -