• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Gao, Yuan (Gao, Yuan.) | Liu, Pengyu (Liu, Pengyu.) | Wu, Yueying (Wu, Yueying.) | Jia, Kebin (Jia, Kebin.) (学者:贾克斌) | Gao, Guandong (Gao, Guandong.)

收录:

Scopus SCIE PubMed

摘要:

high efficiency video coding (HEVC), coding tree contributes to excellent compression performance. However, coding tree brings extremely high computational complexity. Innovative works for improving coding tree to further reduce encoding time are stated in this paper. A novel low complexity coding tree mechanism is proposed for HEVC fast coding unit (CU) encoding. Firstly, this paper makes an in-depth study of the relationship among CU distribution, quantization parameter (QP) and content change (CC). Secondly, a CU coding tree probability model is proposed for modeling and predicting CU distribution. Eventually, a CU coding tree probability update is proposed, aiming to address probabilistic model distortion problems caused by CC. Experimental results show that the proposed low complexity CU coding tree mechanism significantly reduces encoding time by 27% for lossy coding and 42% for visually lossless coding and lossless coding. The proposed low complexity CU coding tree mechanism devotes to improving coding performance under various application conditions.

关键词:

作者机构:

  • [ 1 ] [Gao, Yuan]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 2 ] [Liu, Pengyu]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 3 ] [Wu, Yueying]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 4 ] [Jia, Kebin]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 5 ] [Gao, Guandong]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 6 ] [Gao, Yuan]Beijing Lab Adv Informat Networks, Beijing, Peoples R China
  • [ 7 ] [Liu, Pengyu]Beijing Lab Adv Informat Networks, Beijing, Peoples R China
  • [ 8 ] [Wu, Yueying]Beijing Lab Adv Informat Networks, Beijing, Peoples R China
  • [ 9 ] [Jia, Kebin]Beijing Lab Adv Informat Networks, Beijing, Peoples R China
  • [ 10 ] [Gao, Guandong]Beijing Lab Adv Informat Networks, Beijing, Peoples R China
  • [ 11 ] [Gao, Yuan]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 12 ] [Liu, Pengyu]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 13 ] [Wu, Yueying]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 14 ] [Jia, Kebin]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 15 ] [Gao, Guandong]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China

通讯作者信息:

  • 贾克斌

    [Jia, Kebin]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China;;[Jia, Kebin]Beijing Lab Adv Informat Networks, Beijing, Peoples R China;;[Jia, Kebin]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China

电子邮件地址:

查看成果更多字段

相关关键词:

相关文章:

来源 :

PLOS ONE

ISSN: 1932-6203

年份: 2016

期: 3

卷: 11

3 . 7 0 0

JCR@2022

ESI学科: Multidisciplinary;

ESI高被引阀值:214

中科院分区:3

被引次数:

WoS核心集被引频次: 1

SCOPUS被引频次: 2

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 3

归属院系:

在线人数/总访问数:5723/2950360
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司