MATH/MTHE 477/877
Data Compression and Source Coding
Winter 2012

Announcements | Slides | Homework| Course Outline| Syllabus]

Instructor
Tamas Linder
Office: Jeffery Hall, Room 401
Telephone: 533-2417
E-mail: linder@mast.queensu.ca

Announcements

Lectures
Monday 10:30 am, Wednesday 9:30 am, Friday 8:30 am, Jeffery Hall 115

Office Hours
Tuesday 3:30 - 3:30 pm or by appointment

Homework Assignments
Assignments will be posted on this web site (click here to see them); no paper copies will be handed out. Solutions to the assignments will be on reserve in the Douglas Library.

Course Outline

Text
  • Class notes
  • Lecture slides

    Recommended Text
  • A. Gersho and R. M. Gray, Vector Quantization and Signal Compression, Kluwer, 1992.
  • T. M. Cover and J. A. Thomas, Elements of Information Theory, 2nd Ed., Wiley, 2006.

    Other texts of interest
  • I. Csiszár and P. Shields, Information Theory And Statistics: A Tutorial, Now Publishers, 2004.
  • K. Sayood. Introduction to Data Compression, 3rd ed., Morgan Kauffman, 2006.
  • R.M. Gray, Source Coding Theory, Kluwer, 1990. (Shannon distortion-rate theory and asymptotic quantization theory.)
  • T. Berger, Rate-Distortion Theory, Prentice-Hall, 1971. (The bible on rate-distortion theory.)
  • R.M. Gray and D.L. Neuhoff, "Quantization," IEEE Transactions on Information Theory, vol. 44, pp. 2325-2384, Oct. 1998.
  • J. D. Gibson, T. Berger, T. Lookabaugh, D. Lindbergh, R. L. Baker, Digital Compression for Multimedia, Principles and Standards Morgan Kauffman 1998.
  • A. Moffat and A. Turpin Compression and Coding Algorithms Kluwer, 2002.
  • T.C. Bell, J.G. Cleary, and I.H. Witten, Text Compression, Prentice-Hall, 1990.
  • W.B. Pennebaker and J.L. Mitchell, JPEG: Still Image Data Comrpression Standard, Van Nostrand Reinhold, 1993.
  • J.A. Storer, Data Compression - Methods and Theory, Computer Science Press, NY, 1988.
  • S. Graf and H. Luschgy, Foundations of Quantization for Probability Distributions, Springer, Lecture Notes in Mathematics, 1730, Berlin, 2000.

    Prerequisite
    Information Theory MATH 474/874

    Evaluation
    MATH/MTHE 477 students: Homework 25%, Midterm quizzes 25% + 25% + 25%
    MATH/MTHE 877 students: Homework 25%, Midterm quizzes 15% + 15% + 15%, Final project 30%

    Some recommended web sites