Machine Learning-Based Rate Control Scheme for High Efficiency Video Coding
- Resource Type
- Conference
- Authors
- Hsieh, Jui-Hung; Syu, Jing-Cheng; Zhang, Hui-Lan
- Source
- 2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Intelligent Signal Processing and Communication Systems (ISPACS), 2019 International Symposium on. :1-2 Dec, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
machine learning
motion estimation
rate control
HEVC
- Language
- ISSN
- 2642-3529
The up-and-coming high-efficiency video coding (HEVC) offers superior compression performance compared to the previous-generation video compression standard H.264/AVC. The rate control is the most important coding tool for compressed data transmission because of the time-varying transmission bandwidth. Based on a wide range of offline data analyses and statistics, this paper presents a rapid rate control scheme that has low computational complexity for HEVC applications within electronic devices. Experimental results demonstrate that the presented scheme can perform HEVC under time-varying bit-rate conditions.