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International Conference on Wavelet Analysis and Its Applications

WAA 2001: Wavelet Analysis and Its Applications pp 65–75Cite as

Embedded Zerotree Wavelet Coding of Image Sequence

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2251))

Abstract

In this paper we present an image sequence coding system based on Embedded Zerotree Wavelet algorithm (EZW). Difference between the image in the coder and the reconstructed previous image in the decoder is used as technique for removing the temporal redundancies. The first image is encoded in intra-mode by EZW algorithm and a specific binary codebook CB1. The subsequent images in the sequence are encoded by performing the difference between the reconstructed previous image in the decoder and the current image in the coder; this difference (residual image) is then encoded by EZW algorithm and a specific binary codebook CB2. Simulations are operated on Claire and Alexis sequences. The results show that the system can provides best reconstruction quality as well objectively as subjectively for a minimum given bit rate. Progressive transmission, rate control for constant bit-rate and rate scalability are the main characteristics of this system.

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References

  1. J.M. Shapiro, “Embedded image coding using zerotree of wavelet coefficients”, IEEE Trans. on Signal Processing, Vol.41, No.12, pp.3445–3462, Dec.1993.

    Article  MATH  Google Scholar 

  2. I. Daubechies, “Orthonormal bases of compactly supported wavelets”, Communication on Pure and Applied Mathematics, V.41, pp.909–996, Nov.1988.

    Google Scholar 

  3. S. Mallat, “Atheory for multi-resolution signal decomposition: the wavelet representation”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vo.11, pp.674–693, July 1989.

    Google Scholar 

  4. I. Daubechies, Ten Lectures on Wavelets, SIAM, Philadelphia, PA, 1992.

    Google Scholar 

  5. J.D. Villasenor, B. Belzer, and J. Lio, “Wavelet filter evaluation for image compression”, IEEE Trans. on Image Processing, Vol.4, No.8, pp.1053–1060, Aug.1995.

    Article  Google Scholar 

  6. G. Strang, and T. Nguyen, Wavelets and Filter Banks, Wallesley-Cambridge Press, Wellesley, MA, 1996.

    Google Scholar 

  7. A. Zandi, J.D. Allen, E.L. Schwartz, and M. Boliek, “CREW: Compression with Reversible Embedded wavelet”, IEEE Data Compression Conference, pp.212–221, Snowbird, Mar.1995.

    Google Scholar 

  8. A. Said, and W.A. Pearlman, “An image multi-resolution representation for loss less and lossy compression”, IEEE Trans. on Image Processing, Vol.5, No.9, pp.1303–1310, Sep.1996.

    Article  Google Scholar 

  9. Y. Chen, and W.A. Pearlman, “Three-dimensional subband coding of video using zerotree method”, Proc. SPIE, Visual Communications and Image Processing, pp.1302–1309, Orlando, Mar. 1996.

    Google Scholar 

  10. A. Said, and W.A. Pearlman, “A new fast and efficient image codec based on set partitioning in hierarchical trees”, IEEE Trans. on Circuits and Systems for Video Technology, Vol.6, No.3, pp.243–250, Jun. 1996.

    Article  Google Scholar 

  11. S.A. Martucci, I. Sodagar, T.H. Chiang, and Y.Q. Zhang, “ A zerotree wavelet coder”, IEEE Trans. on Circuits and Systems for Video Technology, Vol.7, No.1, pp.109–118, Feb. 1997.

    Article  Google Scholar 

  12. J. Li, P. Cheng, and C. Kuo, “ On the improvement of embedded zerotree wavelet coding”, Proc. SPIE, Visual Communications and Image Processing, pp.1490–1501, Orlando, Apr. 1995.

    Google Scholar 

  13. H. Man, F. Kossentini, and M. Smith,“Robust EZW image coding for noisy channels”, IEEE Signal Processing Letters, Vol.4, No.8, pp.227–229, Aug. 1997.

    Article  Google Scholar 

  14. C.D. Creusere, “A new method for robust image compression based on the embedded zerotree wavelet algorithm”, IEEE Trans. on Image Processing, Vol.6, No.10, pp.1436–1442, Oct. 1997.

    Article  Google Scholar 

  15. J.K. Rogers, and P.C. Cosman, “Wavelet zerotree image compression with packetization”, IEEE Signal Processing Letters, Vol.5, No.5, pp.105–107, May 1998.

    Article  Google Scholar 

  16. S. Joo, H. Kikuchi, S. Sasaki, and J. Shin, “Flexible Zerotree coding of Wavelet coefficeints”, IEICE Trans. Fundamentals, Vol.E82-A, No.4, Apr. 1999.

    Google Scholar 

  17. Michael W. Marcellin, Michael J. Gormish, Ali Bilgin, and Martin P. Boliek, “ An overview of JPEG-2000”, Proc. IEEE Data Compression Conference, pp.523–541, 2000.

    Google Scholar 

  18. Beong-Jo Kim, and W.A. Pearlman, “An embedded wavelet video coder using three-dimensional set partitioning in hierarchical trees (SPIHT)”, Proc. DCC’97, IEEE Data Compression Conference, pp.251–260, Snowbird, UT, Mar. 1997.

    Google Scholar 

  19. M. Jérôme, “Optimal Image Coding based on Probability Distribution of Embedded Zerotree Wavelet Symbols”, Tunisian-German Conference on Smart Systems and Devices SSD, pp.666–671, Hammamet, Tunisia, March 27–30, 2001.

    Google Scholar 

  20. M. Jérôme et N. Ellouze, “Etude énergétique de l’analyse multi-résolution d’images par ondelette, Proc. in JTEA’2000, Tome1, pp.103–109, 24–25 Mar. 2000 Hammamet, Tunisia.

    Google Scholar 

  21. M. Jérôme and N. Ellouze, “Image Wavelet Coefficients Quantization by Embedded Zerotree Wavelet Algorithm”, Proc. in ACIDCA’2000, International conference on Artificial and Computational Intelligence for Decision, Control and Automation in Engineering and Industrial Applications, pp.1–5, Monastir, 22–24 March 2000.

    Google Scholar 

  22. M. Antoni, M. Barlaud, P. Mathieu, and I. Daiubechies, “Image coding using wavelet transform”, IEEE Trans. on Image Processing, Vol.1, No.2, pp.205–220, Apr. 1992.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Laboratoire de Système et Traitement du Signal (LSTS), Ecole Nationale d’Ingènieurs de Tunis, BP 37, Tunis le Belvédère, 1002, Tunisia

    Mbainaibeye Jérôme & Noureddine Ellouze

Authors
  1. Mbainaibeye Jérôme
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  2. Noureddine Ellouze
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Yuan Y. Tang , Pong C. Yuen  & Chun-hung Li ,  & 

  2. Department of Mathematics, Washington University, Cupples I, Campus Box 1146, 63130, St. Louis, Missouri, USA

    Victor Wickerhauser

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© 2001 Springer-Verlag Berlin Heidelberg

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Jérôme, M., Ellouze, N. (2001). Embedded Zerotree Wavelet Coding of Image Sequence. In: Tang, Y.Y., Yuen, P.C., Li, Ch., Wickerhauser, V. (eds) Wavelet Analysis and Its Applications. WAA 2001. Lecture Notes in Computer Science, vol 2251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45333-4_11

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  • DOI: https://doi.org/10.1007/3-540-45333-4_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43034-6

  • Online ISBN: 978-3-540-45333-8

  • eBook Packages: Springer Book Archive

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