Content classification based reference frame reduction and machine learning based non-square block partition skipping for inter prediction of screen content coding

Yawei Wang, Gaoxing Chen, Takeshi Ikenaga

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Screen Content Coding (SCC) is the extension of the latest video compression standard High Efficiency Video Coding (HEVC). SCC is mainly developed for reducing the bit-rate of videos generated from computers. However, under inter configuration, SCC has large complexity which brings heavy burden to encoding. This paper proposes a content classification based reference frame reduction method and a non-square prediction unit (PU) skipping method to accelerate SCC. In reference frame reduction method, according to number of colors, input coding tree unit (CTUs) will be divided into two classes: natural contents and screen contents. For each class, reference frame can be reduced based on different standard. In PU partition skipping method, five features are extracted from a CTU. The classic learning tool SVM is used to classify CTUs, then six non-square PU partition in depth 1, 2, 3 can be skipped. Finally, 40.83% encoding time saving on average is achieved with only 0.71% BD-rate degradation compared with SCC reference software (SCM6.0).

本文言語English
ホスト出版物のタイトルProceedings - 2017 2nd International Conference on Multimedia and Image Processing, ICMIP 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ240-244
ページ数5
ISBN(電子版)9781509059546
DOI
出版ステータスPublished - 2017 12 15
イベント2nd International Conference on Multimedia and Image Processing, ICMIP 2017 - Wuhan, Hubei, China
継続期間: 2017 3 172017 3 19

出版物シリーズ

名前Proceedings - 2017 2nd International Conference on Multimedia and Image Processing, ICMIP 2017
2017-January

Other

Other2nd International Conference on Multimedia and Image Processing, ICMIP 2017
国/地域China
CityWuhan, Hubei
Period17/3/1717/3/19

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識
  • 信号処理
  • メディア記述

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