A Video Compression Algorithm for ATM Networks with ABR Service, Using Visual Criteria

  • S. Felici
  • J. Martinez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1718)


In this paper 3 is presented an adaptive video compression algorithm designed for the video transmission over best-effort network with services that can adapt to changing network conditions, specifically Available Bit Rate (ABR) services in Asynchronous Transfer Mode (ATM) networks.

The proposed algorithm tries to minimise the impact that cell losses could have on the perceived quality, using perceptual bit allocation procedures and Rate-Distortion minimisation techniques. Furthermore the algorithm adaptively estimates the compression ratio by means of a forecast mechanism based on the value of the feedback signal sent by the network. It should be noticed this algorithm is based on a 3D subband coding that uses wavelet filter banks but it does not use motion estimation with block matching procedures to prevent from error propagation effects.


Video Coder Resolution Level Asynchronous Transfer Mode Asynchronous Transfer Mode Network Functional Block Diagram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Rec. 1371 Traffic Control and Congestion Control in B-ISDN ATM. ITU-T, May 1996.Google Scholar
  2. 2.
    J.R. Vidal J. Martinez and L. Guijarro. A Low Complexity Congestion Control Algorithm for the ABR Class of Service. In Internation Distributed Multimedia Systems IDMS98, Oslo (Norway), pages 219–230, September 1998.Google Scholar
  3. 3.
    C Chou and C Chen. A perceptually optimized 3d subband codec for video communication over wireless channels. IEEE Trans. on Circ. and Syst. Video Tech., 1996.Google Scholar
  4. 4.
    A. Ortega Chi-Yuan Hsu and A. Reibman. Joint Selection of Source and Channel Rate for VBR Video Transmission under ATM Policing Constraints. IEEE Journal on Selected Areas in Commun., 1997.Google Scholar
  5. 5.
    Gilbert Strang and T. Nguyen. Wavelets and Filter Banks. Wellesley-Cambridge Press, USA, 1996.Google Scholar
  6. 6.
    K. R. Rao and J. J. Hwang. Techniques and Standards for Image, Video and Audio Coding. Signal processing series. Prentice Hall, New Jersey, 1996.Google Scholar
  7. 7.
    A. B. Watson. Efficiency of a model human image code. Journal of the Opt. Soc. of Am., 1987.Google Scholar
  8. 8.
    J. Malo A. Pons A. Felipe J. Artigas. Characterization of the human visual system threshold performance by a weighting function in the gabor domain. Journal of Modern Optics, 44(1):127–148, 1997.CrossRefGoogle Scholar
  9. 9.
    P. P. Vaidyanathan. Multirate systems and filter banks. Prentice Hall, 1993.Google Scholar
  10. 10.
    S. Fahmy R. Goyal R. Jain, S. Kalyanaraman and S. Kim. Source Behavior for ATM ABR Traffic Management: An Explanation. IEEE Communications Magazine, 34:50–57, November 1996.Google Scholar
  11. 11.
    Rec. 1363 B-ISDN ATM Adaptation Layer Spec. ITU-T, 1993.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • S. Felici
    • 1
  • J. Martinez
    • 2
  1. 1.Institut de RoboticaUniversistat de ValenciaSpain
  2. 2.Dept. Comunicaciones Universidad PolitecValenciaSpain

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