Hardware friendly background analysis based complexity reduction in H.264/AVC multiple reference frames motion estimation

Yiqing Huang*, Zhenyu Liu, Satosh Goto, Takeshi Ikenaga

*この研究の対応する著者

研究成果: Conference contribution

抄録

In H.264 standard, multiple reference frame motion estimation (MRF-ME) can help to generate small residues and improve the performance. However, MRF-ME is also a computation intensive task for video coding system. Many software oriented fast algorithms have been proposed to shorten MRF-ME process. For hardwired real-time encoder, the division of ME part into two pipeline stages degrades the efficiency of many fast algorithms. This paper gives one hardware friendly MRF-ME algorithm to reduce computation complexity in MRF-ME procedure. The proposed algorithm is based on the analysis of macroblock's (MB's) feature and restricts search range for static background MB. Through experiment results, with negligible video quality degradation, the proposed background analysis based MRF-ME algorithm can averagely reduce 41.75% ME time for sequences with static background. Moreover, the proposed algorithm is compatible to other fast algorithms and friendly to hardware implementation of H.264 real-time encoder.

本文言語English
ホスト出版物のタイトル2007 International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2007 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ594-597
ページ数4
ISBN(印刷版)9781424414475
DOI
出版ステータスPublished - 2007 1 1
イベント2007 International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2007 - Xiamen, China
継続期間: 2007 11 282007 12 1

出版物シリーズ

名前2007 International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2007 - Proceedings

Conference

Conference2007 International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2007
国/地域China
CityXiamen
Period07/11/2807/12/1

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 信号処理
  • ソフトウェア
  • 電子工学および電気工学
  • 数学 (全般)

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