Coding Efficient Motion Estimation Rate Control for H.265/HEVC
- Resource Type
- Conference
- Authors
- Hsieh, Jui-Hung; Syu, Jing-Cheng; Zhang, Zhi-Yu
- Source
- 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) Consumer Electronics (GCCE), 2020 IEEE 9th Global Conference on. :442-443 Oct, 2020
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Transportation
Quantization (signal)
Machine learning algorithms
Motion estimation
Encoding
Real-time systems
Mobile video
Standards
Machine learning
quantization parameter
H.265/HEVC.
- Language
Skillful rate-control inside motion estimation (ME) plays a crucial part in real-time mobile video coding because the available transmission bandwidth in mobile video coding applications within handhold devices is time-varying instead of fixed in the video coding standard H.264/AVC or H.265/high efficiency video coding (HEVC). Rate control consists of coding bit allocation and quantization parameter selection, which are difficult to implement in hardware. To overcome this issue, this paper achieves an ME rate control design on the basis of the improved machine learning (ML) scheme, and the auxiliary experimental outcomes reveal the coding effectiveness and feasibility of the proposed method.