Video Compression

  • Lingfen Sun
  • Is-Haka Mkwawa
  • Emmanuel Jammeh
  • Emmanuel Ifeachor
Part of the Computer Communications and Networks book series (CCN)

Abstract

Compression in VoIP is the technical term which refers to the reduction of the size and bandwidth requirement of voice and video data. In VoIP, ensuring acceptable voice and video quality is critical for acceptance and success. However, quality is critically dependent on the compression method and on the sensitivity of the compressed bitstream to transmission impairments. An understanding of standard voice and video compression techniques, encoders and decoders (codecs) is necessary in order to design robust VoIP applications that ensure reliable and acceptable quality of delivery. This understanding of the techniques and issues with compression is important to ensure that appropriate codecs are selected and configured properly. This chapter firstly introduces the need for media compression and then explains some basic concepts for video compression, such as video signal representation, resolution, frame rate, lossless and lossy video compression. This is followed by video compression techniques including predictive coding, quantisation, transform coding and interframe coding. The chapter finally describes the standards in video compression, e.g. H.120, H.261, MPEG1&2, H.263, MPEG4, H.264 and the latest HEVC (High Efficiency Video Coding) standard.

Keywords

Entropy Europe Aliasing 

References

  1. 1.
    Chen W, Smith C, Fralick S (1979) A fast computational algorithm for the discrete cosine transform. IEEE Trans Commun 1004–1009 Google Scholar
  2. 2.
    Choi H, Nam J, Sim D, Bajic IV (2011) Scalable video coding based on high efficiency video coding (HEVC). In: Proceedings of 2011 IEEE Pacific Rim conference on communications, computers and signal processing (PacRim), pp 346–351 Google Scholar
  3. 3.
    Encoding parameters of digital television for studios, digital methods of transmitting television information. ITU-R BT.601 (2011) Google Scholar
  4. 4.
    Ghanbari M (2003) Standard codecs image compression to advanced video coding. IEE, London. ISBN:0-85296-0-710-2 Google Scholar
  5. 5.
    Huffman D (1952) A method for the construction of minimum redundancy codes. In: Procedure of the IRE 40, pp 1098–1101 Google Scholar
  6. 6.
    ITU-T (1993) Video codec for audiovisual services at p×64 kbit/s. ITU-T H.261 Google Scholar
  7. 7.
    ITU-T (1996) Video coding for low bit rate communication. ITU-T H.263 Google Scholar
  8. 8.
    ITU-T (2003) Advanced video coding for generic audiovisual services. ITU-T H.264 Google Scholar
  9. 9.
    Jain AK (1989) The fundamentals of digital image processing. Prentice Hall, New York Google Scholar
  10. 10.
    Jayant NS, Noll P (1984) Digital coding of waveforms: principles and applications to speech and video. Prentice Hall, London Google Scholar
  11. 11.
    MPEG-1: Coding of moving pictures and associated audio for digital storage media at up to about 1.5 Mbit/s. ISO/IEC (1991) Google Scholar
  12. 12.
    Netrali AN, Haskell BG (1988) Digital pictures: representation and compression. Plenum, New York Google Scholar
  13. 13.
    Oppenheim AV, Schafer RW (1990) Discrete-time signal processing. Prentice Hall, New York Google Scholar
  14. 14.
    Rosdiana E (2000) Transmission of transcoded video over ABR networks. Master’s thesis, University of Essex Google Scholar
  15. 15.
    Symes P (1998) Video compression. McGraw Hill, New York. ISBN:0-07-063344-4 Google Scholar
  16. 16.
    Witten IH, Neal RM, Cleary JG (1987) Arithmetic coding for data compression. Commun ACM 520–540 Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Lingfen Sun
    • 1
  • Is-Haka Mkwawa
    • 1
  • Emmanuel Jammeh
    • 1
  • Emmanuel Ifeachor
    • 1
  1. 1.School of Computing and MathematicsUniversity of PlymouthPlymouthUK

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