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Dynamic motion vector refreshing for enhanced error resilience in HEVC

conference contribution
posted on 10.10.2016 by Joao F.M. Carreira, Varuna De Silva, Erhan Ekmekcioglu, Ahmet Kondoz, Pedro A.A. Assuncao, Sergio M.M. Faria
The high level of compression efficiency achieved by HEVC coding techniques decreases the error resilience performance under error prone conditions. This paper addresses the error resiliency of the HEVC standard, focusing on the new motion estimation tools. It is shown that the temporal dependency of motion information is comparatively higher than that in the H.264/AVC standard, causing an increase in the error propagation. Based on this evidence, this paper proposes a method to make intelligent use of temporal motion vector (MV) candidates during the motion estimation process, in order to decrease the temporal dependency, and improve the error resiliency without penalising the rate-distortion performance. The simulation results show that the proposed method improves the error resilience under tested conditions by increasing the video quality by up to 1.7 dB in average, compared to the reference method that always enables temporal MV candidates.

Funding

This work was supported by the Fundação para a Ciência e a Tecnologia, Portugal (under the PhD grant SFRH/BD/86368/2012), and the ROMEO project (grant number: 287896), which was funded by the EC FP7 ICT collaborative research programme.

History

School

  • Loughborough University London

Published in

Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 22nd European

Pages

281 - 285

Citation

CARREIRA, J. ... et al., 2014. Dynamic motion vector refreshing for enhanced error resilience in HEVC. IN: Proceedings of the 2013 22nd IEEE European Signal Processing Conference (EUSIPCO 2013), Lisbon, Portugal, 1-5 September 2013, pp.281-285.

Publisher

© IEEE

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2014

Notes

Closed access.

ISBN

9780992862619

ISSN

2076-1465

Book series

INSPEC accession no.;14775429

Language

en

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