Advertisement

Multimedia Tools and Applications

, Volume 58, Issue 3, pp 569–583 | Cite as

Multiresolution, perceptual and vector quantization based video codec

  • Akbar Sheikh AkbariEmail author
  • Pooneh Bagheri Zadeh
  • Tom Buggy
  • John Soraghan
Article
  • 119 Downloads

Abstract

This paper presents a novel Multiresolution, Perceptual and Vector Quantization (MPVQ) based video coding scheme. In the intra-frame mode of operation, a wavelet transform is applied to the input frame and decorrelates it into its frequency subbands. The coefficients in each detail subband are pixel quantized using a uniform quantization factor divided by the perceptual weighting factor of that subband. The quantized coefficients are finally coded using a quadtree-coding algorithm. Perceptual weights are specifically calculated for the centre of each detail subband. In the inter-frame mode of operation, a Displaced Frame Difference (DFD) is first generated using an overlapped block motion estimation/compensation technique. A wavelet transform is then applied on the DFD and converts it into its frequency subbands. The detail subbands are finally vector quantized using an Adaptive Vector Quantization (AVQ) scheme. To evaluate the performance of the proposed codec, the proposed codec and the adaptive subband vector quantization coding scheme (ASVQ), which has been shown to outperform H.263 at all bitrates, were applied to six test sequences. Experimental results indicate that the proposed codec outperforms the ASVQ subjectively and objectively at all bit rates.

Keywords

Perceptual weights Wavelet transforms Vector quantization and video codec 

References

  1. 1.
    Al-Hudhud G (2009) Adaptation of HVS sensitivity for perceptual modelling of wavelet-based image compression. International Conference in Visualisation, pp 196–200Google Scholar
  2. 2.
    Antonini M, Barlaud M, Mathieu P, Daubechies I (1992) Image coding using the wavelet transform. IEEE Trans Image Process 1(No. 2):205–220CrossRefGoogle Scholar
  3. 3.
    Ashraf G, Chong MN (1997) Performance analysis of H.261 and H.263 video coding algorithms. IEEE International Symposium on Consumer Electronics ISCE ‘97, pp 153–156Google Scholar
  4. 4.
    Bradley AP (1999) A wavelet visible difference predictor. IEEE Trans Image Process, 8(no. 5)Google Scholar
  5. 5.
    Fraunhofer, Institut Nachrichtentechnik Heinrich-Hertz-Institute, H.264/AVC software version: JM 17.2. Available from: http://iphome.hhi.de/suehring/tml/ [accessed 16/11/2010]
  6. 6.
    Ghanbari M (1999) Video coding an introduction to standard codecs. The Institution of Electrical Engineering, LondonGoogle Scholar
  7. 7.
    HSontsch I, Karam LJ (2000) Locally adaptive perceptual image coding. IEEE Trans Image Process 9(9):1472–1483MathSciNetCrossRefGoogle Scholar
  8. 8.
    Kaia X, Jiea Y, Minb ZY, Lianga LX (2005) HVS-based medical image compression. Eur J Radiol 55:139–145CrossRefGoogle Scholar
  9. 9.
    Katto J, Ohki J, Nogaki S, Ohta M (1994) A wavelet codec with overlapped motion compensation for very low bit-rate environment. IEEE Trans Circuits Syst Video Technol 4(3):328–338CrossRefGoogle Scholar
  10. 10.
    Lin M, Ngan KN (2010) Adaptive block-size transform based just-noticeable difference profile for videos. IEEE International Symposium on Circuits and Systems (ISCAS), pp 4213–4216Google Scholar
  11. 11.
    Maalouf A, Larabi M–C (2010) A no-reference color video quality metric based on a 3D multispectral wavelet transform. International Workshop on Quality of Multimedia Experience (QoMEX), pp 11–16Google Scholar
  12. 12.
    Murat Tekalp A (1995) Digital video processing. Prentice-Hall, ISBN: 0-13-190075-7Google Scholar
  13. 13.
    Nadenau MJ, Reichel J (2003) Wavelet-based color image compression: Exploiting the contrast sensitivity function. IEEE Trans Image Process, 12(no. 1), JanuaryGoogle Scholar
  14. 14.
    Ostermann J, Bormans J, List P, Marpe D, Narroschke M, Pereira F, Stockhammer T, Wedi T (2004) Video coding with H.264/AVC: Tools, performance, and complexity. IEEE Circuits Syst Mag 4:7–28CrossRefGoogle Scholar
  15. 15.
    Pastuszak G (2005) A high-performance architecture for embedded block coding in JPEG 2000. IEEE Trans Circuit Syst Video Technol, 15(no. 9), SeptemberGoogle Scholar
  16. 16.
    Samet H (1984) The quadtree and related hierarchical data structures. ACM Comput Surv, 16(no. 2), JuneGoogle Scholar
  17. 17.
    Sheikh Akbari A, Soraghan JJ (2003) Adaptive joint subband vector quantisation codec for handheld videophone applications. IEE Electr Lett 39(no.14):1044–1046CrossRefGoogle Scholar
  18. 18.
    Skodras A, Christopoulos Ch, Ebrahimi T (2001) The JPEG 2000 still image compression standard. IEEE Signal Process Mag, 18(no. 5), SeptemberGoogle Scholar
  19. 19.
    Taubman D (2000) High performance scalable image compression with EBCOT. IEEE Trans Image Process, 9(no. 7)Google Scholar
  20. 20.
    Taubman DS, Marcellin MW (2004) JPEG 2000 image compression fundamentals, standard and practice. Kluwer Academic Publisher, MassachusettsGoogle Scholar
  21. 21.
    Van Dyck RE, Rajala SA (1994) Subband/VQ coding of colour images with perceptually optimal bit allocation. IEEE Trans Circuit Syst Video Technol, 4(no. 1), FebruaryGoogle Scholar
  22. 22.
    Voukelatos SP, Soraghan JJ (1997) Very low bit rate color video coding using adaptive subband vector quantization with dynamic bit allocation. IEEE Trans Circuit Syst Video Technol 7(2):424–428CrossRefGoogle Scholar
  23. 23.
    Yang X, Lin W, Lu Z (2005) Motion-compensated residue preprocessing in video coding based on just-noticeable-distortion profile. IEEE Trans Circuits Syst Video Technol, 15(no. 6), JuneGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Akbar Sheikh Akbari
    • 1
    Email author
  • Pooneh Bagheri Zadeh
    • 2
  • Tom Buggy
    • 3
  • John Soraghan
    • 4
  1. 1.Faculty of Computing, Engineering and TechnologyStaffordshire UniversityStaffordUK
  2. 2.Department of Engineering, Faculty of TechnologyDe Montfort UniversityLeicesterUK
  3. 3.Division of Communications, Networking and Electronics Engineering, School of Engineering & ComputingGlasgow Caledonian UniversityGlasgowUK
  4. 4.Institute of Communications and Signal Processing, Department of Electronic & Electrical EngineeringUniversity of StrathclydeGlasgowUK

Personalised recommendations