A fast mode decision algorithm applied to coarse-grain quality scalable video coding

Wang, D; Yuan, C; Sun, Y; Zhang, J; Jin, X

A fast mode decision algorithm applied to coarse-grain quality scalable video coding

Wang, D Yuan, C Sun, Y Zhang, J

Jin, X

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Publication Type:: Journal Article
Citation:: Journal of Visual Communication and Image Representation, 2014, 25 (7), pp. 1631 - 1639
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Wang, D	en_US
dc.contributor.author	Yuan, C	en_US
dc.contributor.author	Sun, Y	en_US
dc.contributor.author	Zhang, J https://orcid.org/0000-0002-7240-3541	en_US
dc.contributor.author	Jin, X	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Journal of Visual Communication and Image Representation, 2014, 25 (7), pp. 1631 - 1639	en_US
dc.identifier.issn	1047-3203	en_US
dc.identifier.uri	http://hdl.handle.net/10453/35494
dc.description.abstract	© 2014 Elsevier Inc. All rights reserved. A fast mode decision algorithm is proposed for a Coarse-Grain Scalable (CGS) video encoder based on the encoding characteristics of quality Scalable Video Coding (SVC). First, candidate modes and coding orders are predicted, based on inter-layer and spatial correlations. Three early termination methods are then proposed based on CGS encoding structure. Finally, all candidate modes are checked sequentially, according to their predicted order with three early termination conditions, to improve the coding speed. Experimental results have demonstrated that the proposed algorithm could reduce the encoding time by an average of 84.39%, with negligible coding efficiency losses.	en_US
dc.relation.ispartof	Journal of Visual Communication and Image Representation	en_US
dc.relation.isbasedon	10.1016/j.jvcir.2014.07.006	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A fast mode decision algorithm applied to coarse-grain quality scalable video coding	en_US
dc.type	Journal Article
utslib.citation.volume	7	en_US
utslib.citation.volume	25	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	1203 Design Practice and Management	en_US
utslib.for	1905 Visual Arts and Crafts	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.issue	7	en_US
pubs.publication-status	Published	en_US
pubs.volume	25	en_US

Abstract:

© 2014 Elsevier Inc. All rights reserved. A fast mode decision algorithm is proposed for a Coarse-Grain Scalable (CGS) video encoder based on the encoding characteristics of quality Scalable Video Coding (SVC). First, candidate modes and coding orders are predicted, based on inter-layer and spatial correlations. Three early termination methods are then proposed based on CGS encoding structure. Finally, all candidate modes are checked sequentially, according to their predicted order with three early termination conditions, to improve the coding speed. Experimental results have demonstrated that the proposed algorithm could reduce the encoding time by an average of 84.39%, with negligible coding efficiency losses.

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http://hdl.handle.net/10453/35494