Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/16471
Title: Edge oriented block motion estimation for video coding
Authors: Chan, YL 
Siu, WC 
Keywords: Motion estimation
Video coding
Issue Date: 1997
Publisher: The Institution of Engineering and Technology
Source: IEE proceedings. Vision, image, and signal processing, 1997, v. 144, no. 3, p. 136-144 How to cite?
Journal: IEE proceedings. Vision, image, and signal processing 
Abstract: Intensity-based block motion estimation and compensation algorithms are widely used to exploit temporal redundancies in video coding, although they suffer from several drawbacks. One of the problems is that blocks located on boundaries of moving objects are not estimated accurately. It causes poor motion-compensated prediction along the moving edges to which the human visual system is very sensitive. By considering the characteristics of block motions for typical image sequences, an intelligent classifier is proposed to separate blocks containing moving edges to improve on conventional intensity-based block matching approaches. The motion vectors of these blocks are computed using edge matching techniques, so that the motion-compensated frames are tied more closely to the physical features. The proposed method can then make use of this accurate motion information for edge blocks to compute the remaining non-edged blocks. Consequently, a fast and efficient block motion estimation algorithm is developed. s 'Experimental results show that this approach gives a significant improvement in accuracy for motioncompensated frames and computational complexity, in comparison with the traditional intensity-based block motion estimation methods.
URI: http://hdl.handle.net/10397/16471
ISSN: 1350-245X
EISSN: 1359-7108
DOI: 10.1049/ip-vis:19971199
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

31
Last Week
0
Last month
0
Citations as of Aug 17, 2017

WEB OF SCIENCETM
Citations

21
Last Week
0
Last month
0
Citations as of Aug 21, 2017

Page view(s)

55
Last Week
1
Last month
Checked on Aug 20, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.