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Abstract
In this work, we propose a novel rate control algorithm for Versatile Video Coding (VVC) standard based on its distinct rate-distortion characteristics. By modelling the transform coefficients with the composite Cauchy distribution, higher accuracy compared with traditional distributions has been achieved. Based on the transform coefficient modelling, the theoretically derived R-Q and D-Q models which have been shown to deliver higher accuracy in characterizing RD characteristics for sequences with different content are incorporated into the rate control process. Furthermore, to establish an adaptive bit allocation scheme, the dependency between different levels of frames is modelled by a dependency factor to describe relationship between the reference and to-be-coded frames. Given the derived R-Q and D-Q relationships, as well as the dependency factor, an adaptive bit allocation scheme is developed for optimal bits allocation. We implement the proposed algorithm on VVC Test Model (VTM) 3.0. Experiments show that due to proper bit allocation, for low delay configuration the proposed algorithm can achieve 1.03% BD-Rate saving compared with the default rate control algorithm and 2.96% BD-Rate saving compared with fixed-QP scheme. Moreover, 1.29% BD-Rate saving and higher control accuracy have also been observed under the random access configuration.
| Original language | English |
|---|---|
| Pages (from-to) | 2371-2384 |
| Journal | IEEE Transactions on Circuits and Systems for Video Technology |
| Volume | 32 |
| Issue number | 4 |
| Online published | 29 Jun 2021 |
| DOIs | |
| Publication status | Published - Apr 2022 |
Research Keywords
- Adaptation models
- Bit rate
- Distortion
- distortion model
- Encoding
- Quantization (signal)
- rate control
- rate model
- Transforms
- Versatile video coding
- Video coding
RGC Funding Information
- RGC-funded
Fingerprint
Dive into the research topics of 'High Efficiency Rate Control for Versatile Video Coding Based on Composite Cauchy Distribution'. Together they form a unique fingerprint.Projects
- 4 Finished
-
GRF: Adaptive Dynamic Range Enhancement Oriented to High Dynamic Display
KWONG, T. W. S. (Principal Investigator / Project Coordinator), KUO, J. (Co-Investigator), WANG, S. (Co-Investigator) & Zhang, X. (Co-Investigator)
1/01/21 → 5/09/23
Project: Research
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GRF: Towards Smart Visual Sensor Data Representation with Intelligent Sensing in the Internet of Video Things
WANG, S. (Principal Investigator / Project Coordinator), Huang, T. (Co-Investigator) & XUE, C. J. (Co-Investigator)
1/01/21 → 23/06/25
Project: Research
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GRF: Intelligent Ultra High Definition Video Encoder Optimization for Future Versatile Video Coding
KWONG, T. W. S. (Principal Investigator / Project Coordinator), KUO, J. (Co-Investigator), WANG, S. (Co-Investigator) & ZHOU, M. (Co-Investigator)
1/01/20 → 5/09/23
Project: Research
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