Adaptive subsampling and motion feature based fast H.264 motion estimation

Yiqing Huang, Qin Liu, Satoshi Goto, Takeshi Ikenaga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The latest video coding standard H.264/AVC can provide excellent performance compared with previous standards. However, the introduction of new techniques in motion estimation also brings about heavy burden of computation complexity on the video coding system. In hardware field, the subsampling technique is widely used to reduce hardware cost and release computation burden of ME engine. However, direct subsampling on video sequences will cause serious quality degradation. This paper proposes a hardware friendly fast ME algorithm which combines two complexity reduction schemes. Firstly, the pixel difference based adaptive subsampling scheme select different subsampling patterns according to the feature of current MB. Secondly, in order to fasten the ME procedure, a search position based 3-layer search range adjustment scheme is proposed to remove redundant search points. Experimental results show that about 74.17% to 90.26% ME Time can be reduced while the video quality loss is trivial. Moreover, since the two schemes are both friendly to hardware implementation, the proposed fast ME algorithm can be implanted into realtime hardwired video coding system.

Original languageEnglish
Title of host publicationProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Pages671-675
Number of pages5
DOIs
Publication statusPublished - 2008 Sep 24
Event1st International Congress on Image and Signal Processing, CISP 2008 - Sanya, Hainan, China
Duration: 2008 May 272008 May 30

Publication series

NameProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Volume2

Conference

Conference1st International Congress on Image and Signal Processing, CISP 2008
CountryChina
CitySanya, Hainan
Period08/5/2708/5/30

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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