Data Compression, Texas A&M University

Texas A&M University ELEN 663: Data Compression, Fall'09

Coordinator: Zixiang Xiong, WERC 244C, zx@ece.tamu.edu, 862-8683
Description: This course presents a comprehensive overview of the theory and practice in source coding. One objective is to survey data compression standards such as MP3, AAC, JPEG, JPEG2000, MPEG-1/2/4 and H.264/AVC. Another is to introduce topics such as joint source-channel coding and distributed source coding to students who are interested in doing research.

Class project: The class project will be done individually or in groups. Each project requires a proposal, classroom presentation and a final report.

Prerequisites: ELEN 644, 646, 647 or permission of the Coordinator.
Class Time and location: TTR 5:30-6:45pm, Zach 223B

Textbook: D. Taubman and M. Marcellin, JPEG2000: Image Compression Fundamentals, Standards, and Practice, Kluwer , 2001.

Reference books and class website:

  • A. Gersho and R. Gray, Vector Quantization and Signal Compression, Kluwer, 1992.
  • Y. Wang, J. Ostermann, and Y.-Q. Zhang, Video Processing and Communications, Prentice Hall, 2001.
  • EE368B-Image and Video Compression at Stanford

    Required reading:

  • R. Gray and D. Neuhoff, "Quantization," IEEE Trans. Information Theory, vol. 44, pp. 2325-2383, October 1998.
  • M. Marcellin and T. Fischer, "Trellis coded quantization of memoryless and Gaussian-Markov sources," IEEE Trans. Communications, vol. 38, pp. 82-93, January, 1990.
  • T. Painter and A. S. Spanias, "Perceptual coding of digital audio," Proc. of the IEEE, vol. 88, pp. 451-513, April 2000.
  • K. Brandenburg, O. Kunz, and A. Sugiyama, "MPEG-4 natural audio coding," Signal Processing: Image communication, vol. 15, pp. 423-444, January 2000.
  • A. Said and W. A. Pearlman, "A new, fast, and efficient image codec based on set partitioning in hierarchical trees," IEEE Trans. Circuits and Systems for Video Technology, vol. 6, pp. 243-250, June 1996.
  • Z. Xiong and K. Ramchandran, "Wavelet image compression," Handbook of Image and Video Processing, A. Bovik, ed., 2nd edition, Academic Press, 2005.
  • R. Hamzaoui, V. Stankovic, and Z. Xiong, ``Efficient rate-distortion based error protection for scalable image bitstreams," IEEE Signal Processing Magazine, vol. 22, pp. 91-107, November 2005.
  • Special Issue on Advances in Video Coding and Delivery, Proceedings of the IEEE, vol. 93, January 2005.
  • D. Slepian and J. Wolf, "Noiseless coding of correlated information sources," IEEE Trans. Inform. Theory, vol. 19, pp. 471-480, July 1973.
  • A. Wyner and J. Ziv, The rate-distortion function for source coding with side information at the decoder," IEEE Trans. Inform. Theory, vol. 22, pp. 1-10, January 1976.
  • Y. Oohama, ``Gaussian multiterminal source coding," IEEE Trans. Inform. Theory, vol. 43, pp. 1912-1923, November 1997.
  • Y. Oohama, "Rate-distortion theory for Gaussian multiterminal source coding systems with several side informations at the decoder," IEEE Trans. Inform. Theory, vol. 38, pp. 2577-2593, July 2005.
  • A. Wagner, S. Tavildar, and P. Viswanath, ``The rate region of the quadratic Gaussian two-terminal sourcecoding problem," IEEE Trans. Inform. Theory, vol. 54, pp. 1938-1961, May 2008.
  • R. Zamir, S. Shamai, and U. Erez, "Nested linear/lattice codes for structured multiterminal binning," IEEE Trans. Inform. Theory, vol. 48, pp. 1250-1276, June 2002.
  • Z. Xiong, A. Liveris, and S. Cheng, ``Distributed source coding for sensor networks," IEEE Signal Processing Magazine, vol. 21, pp. 80-94, September 2004.

    Grading:

  • 25% Problem sets; 25% Midterm exam; 50% Class project