Computational complexity reduction for HEVC intra prediction with SVM

Han Yuan Hsu, Shang En Huang, Yinyi Lin

研究成果: 書貢獻/報告類型會議論文篇章同行評審

5 引文 斯高帕斯(Scopus)

摘要

Unlike most researches focus on computation reduction, the fast algorithm proposed in this paper aims at maintaining the coding efficiency as high as possible. In the proposed algorithm we employ support vector machine (SVM) that uses three parameters as features: variances, low-frequency AC components of DCT and spatially neighboring CU levels for fast CU size decision. In addition, based upon RMD cost we propose an adaptive mode candidates method for further RDO computation. Experimental results demonstrate that average 22% reduction of computational complexity can be achieved but only with 0.09% BD bit rate increase.

原文???core.languages.en_GB???
主出版物標題2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1-2
頁數2
ISBN(電子)9781509040452
DOIs
出版狀態已出版 - 19 12月 2017
事件6th IEEE Global Conference on Consumer Electronics, GCCE 2017 - Nagoya, Japan
持續時間: 24 10月 201727 10月 2017

出版系列

名字2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
2017-January

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???6th IEEE Global Conference on Consumer Electronics, GCCE 2017
國家/地區Japan
城市Nagoya
期間24/10/1727/10/17

指紋

深入研究「Computational complexity reduction for HEVC intra prediction with SVM」主題。共同形成了獨特的指紋。

引用此