Neural network-based arithmetic coding of intra prediction modes in HEVC

By Rui Song, Dong Liu, Houqiang Li, Feng Wu. 2017

78 citations recorded by the source corpus.

In both H.264 and HEVC, context-adaptive binary arithmetic coding (CABAC) is adopted as the entropy coding method. CABAC relies on manually designed binarization processes as well as handcrafted context models, which may restrict the compression efficiency. In this paper, we propose an arithmetic coding strategy by training neural networks, and make preliminary studies on coding of the intra prediction modes in HEVC. Instead of binarization, we propose to directly estimate the probability distribution of the 35 intra prediction modes with the adoption of a multi-level arithmetic codec. Instead of handcrafted context models, we utilize convolutional neural network (CNN) to perform the probability estimation. Simulation results show that our proposed arithmetic coding leads to as high as 9.9% bits saving compared with CABAC.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Xiaogang Wang
3. Wanli Ouyang
4. Trevor Darrell
5. Dacheng Tao
6. Yi Yang
7. Ming-Hsuan Yang
8. Jitendra Malik

In Signal Processing

1. Guo Lu
2. Shanshe Wang
3. Oren Rippel
4. Lubomir D. Bourdev
5. Shiqi Wang
6. Siwei Ma
7. Wanli Ouyang
8. Xinfeng Zhang

Citations in the corpus

• Learned Video Compression (2018, background): “These include improved motion compensation and interpolation [54, 21, 58, 31], intra-prediction coding [40], post-processing refinement [7, 55, 26, 56, 48, 57, 41, 17], and rate control [28].”
• DVC: An End-To-End Deep Video Compression Framework (2018, methodology): “For the video compression task, a lot of DNN based methods have been proposed for intra prediction and residual coding[13], mode decision [22], entropy coding [30], post-processing [23].”
• Image and Video Compression With Neural Networks: A Review (2019, methodology): “improved the CABAC performance on compressing the syntax elements of 35 intra prediction modes by leveraging CNN to directly predict the probability distribution of intra modes instead of the handcrafted context models [96].”