Fast Coding Unit Decision for Intra Screen Content Coding Based on Ensemble Learning

Yali XUE, Xu WANG, Linwei ZHU, Zhaoqing PAN, Sam KWONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

9 Citations (Scopus)


The Screen Content Coding (SCC) is an extension of High Efficiency Video Coding (HEVC), and it achieves significant improvement on compression ratio. However, the obtained coding efficiency is at the cost of high computational complexity. In this paper, to reduce the computation complexity, we propose to use an ensemble classifier for predicting the coding unit (CU) in intra-coding. Firstly, the L1-loss based linear support vector machine (SVM) is employed as basic classifier for its simplicity. Then, a bagging scheme is applied to train the linear classifiers and boost the prediction accuracy by ensemble learning. Compared with the reference software SCM-5.0, the proposed scheme can achieve 30% complexity reduction on average with only 1.64% bit rates increase.
Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication statusPublished - 2019
Externally publishedYes

Bibliographical note

This work was supported in part by the National Natural Science Foundation of China under Grant 61871270, 61672443 and 61620106008, in part by the Guangdong Nature Science Foundation under Grant 2016A030310058, in part by the Shenzhen Emerging Industries of the Strategic Basic Research Project under Grants JCYJ20160226191842793, in part by the Natural Science Foundation of SZU (grant no. 827000144).


  • Coding Unit Decision
  • Ensemble Learning
  • Intra Coding
  • Linear Classification
  • Screen Content Coding


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