CNN-based approach for visual quality improvement on HEVC
- Resource Type
- Conference
- Authors
- Lee, Young-woon; Kim, Ji-hae; Choi, Young-ju; Kim, Byung-gyu
- Source
- 2018 IEEE International Conference on Consumer Electronics (ICCE) Consumer Electronics (ICCE), 2018 IEEE International Conference on. :1-3 Jan, 2018
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Encoding
Image coding
Convolution
Training
Convolutional codes
Standards
Convolutional neural networks
H.265
HEVC
Convolutional Neural Network
- Language
- ISSN
- 2158-4001
Deep learning based on Convolutional Neural Network (CNN) is a very hot issue for various recognition problems. In this paper, we propose a scheme to improve the visual quality of the video coding standard. We apply a CNN model to high efficiency video coding (HEVC) encoding system and suggest a combined coding scheme using a CNN model. Through experiment, we verify that the proposed scheme achieves up to 0.24 dB of the quality improvement on HM 16.10 reference software.