An efficient error concealment algorithm for H.264/AVC using regression modeling-based prediction

Chen, X; Chung, YY; Bae, C; He, X; Yeh, WC

An efficient error concealment algorithm for H.264/AVC using regression modeling-based prediction

Chen, X Chung, YY Bae, C He, X

Yeh, WC

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Consumer Electronics, 2010, 56 (4), pp. 2694 - 2701
Issue Date:: 2010-11-01

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Field	Value	Language
dc.contributor.author	Chen, X	en_US
dc.contributor.author	Chung, YY	en_US
dc.contributor.author	Bae, C	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Yeh, WC	en_US
dc.date.issued	2010-11-01	en_US
dc.identifier.citation	IEEE Transactions on Consumer Electronics, 2010, 56 (4), pp. 2694 - 2701	en_US
dc.identifier.issn	0098-3063	en_US
dc.identifier.uri	http://hdl.handle.net/10453/13623
dc.identifier.uri	http://hdl.handle.net/10453/34154
dc.description.abstract	This paper presents a novel error concealment algorithm for H.264/AVC based on a regression model, which is constructed according to the spatial relationship between block locations and their motion activities. With the proposed algorithm, a corrupted macroblock is partitioned into subblocks and the motion vector of each sub-block is predicted through the regression model with the help of the neighbor motion vectors. The experimental results show that the proposed algorithm can achieve significant Peak Signal Noise Ratio (PSNR) improvement over existing methods with even reduced complexity. The implementation of the proposed algorithm is very simple and therefore it can be readily applied to real-time video applications running on various consumer electronic products such as mobile devices. © 2006 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Consumer Electronics	en_US
dc.relation.isbasedon	10.1109/TCE.2010.5681158	en_US
dc.subject.classification	Networking & Telecommunications	en_US
dc.title	An efficient error concealment algorithm for H.264/AVC using regression modeling-based prediction	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	56	en_US
utslib.for	1005 Communications Technologies	en_US
utslib.for	0906 Electrical and Electronic Engineering	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/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	56	en_US

Abstract:

This paper presents a novel error concealment algorithm for H.264/AVC based on a regression model, which is constructed according to the spatial relationship between block locations and their motion activities. With the proposed algorithm, a corrupted macroblock is partitioned into subblocks and the motion vector of each sub-block is predicted through the regression model with the help of the neighbor motion vectors. The experimental results show that the proposed algorithm can achieve significant Peak Signal Noise Ratio (PSNR) improvement over existing methods with even reduced complexity. The implementation of the proposed algorithm is very simple and therefore it can be readily applied to real-time video applications running on various consumer electronic products such as mobile devices. © 2006 IEEE.

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http://hdl.handle.net/10453/13623