Telecommunication Systems

, Volume 61, Issue 1, pp 21–41 | Cite as

Temporal video transcoding from H.264/AVC-to-SVC for digital TV broadcasting

  • R. Garrido-CantosEmail author
  • J. De Cock
  • J. L. Martinez
  • S. Van Leuven
  • P. Cuenca
  • A. Garrido


Mobile digital TV environments demand flexible video compression like scalable video coding (SVC) because of varying bandwidths and devices. Since existing infrastructures highly rely on H.264/AVC video compression, network providers could adapt the current H.264/AVC encoded video to SVC. This adaptation needs to be done efficiently to reduce processing power and operational cost. This paper proposes two techniques to convert an H.264/AVC bitstream in Baseline (P-pictures based) and Main Profile (B-pictures based) without scalability to a scalable bitstream with temporal scalability as part of a framework for low-complexity video adaptation for digital TV broadcasting. Our approaches are based on accelerating the interprediction, focusing on reducing the coding complexity of mode decision and motion estimation tasks of the encoder stage by using information available after the H.264/AVC decoding stage. The results show that when our techniques are applied, the complexity is reduced by 98 % while maintaining coding efficiency.


Mobile digital TV Videoadaptation  Data mining  H.264/AVC Scalable video coding (SVC) Temporal scalability 



This work was supported by the Spanish MEC and MICINN funds, under the Grant TIN2012-38341-C04-04. The first author would also like to thank Spanish Public Employment Service for its funding support.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • R. Garrido-Cantos
    • 1
    Email author
  • J. De Cock
    • 2
  • J. L. Martinez
    • 1
  • S. Van Leuven
    • 2
  • P. Cuenca
    • 1
  • A. Garrido
    • 1
  1. 1.Albacete Research Institute of InformaticsUniversity of Castilla-La ManchaAlbaceteSpain
  2. 2.Multimedia Lab, Department of Electronics and Information SystemsGhent University-iMindsGhentBelgium

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