Why Isn't the "World Wide Wait" Even Longer?

The answer is image compression.  Modern mathematics (developed in the last 20 years), electrical engineering (DSP) and computer science have been responsible for the development of good image compression algorithms. The course will cover the mathematical basis of many of the ideas behind image processing such as filtering, filter banks, the discrete Fourier and cosine transforms and the discrete wavelet transform. All of this will be balanced by concrete applications of  these ideas to various image processing problems with a special emphasis on image compression. The images help make the mathematics more concrete, as the two pictorial illustrations of Discrete Cosine Transform (DCT) based JPEG compression  and Discrete Wavelet Transform (DWT) based JPEG compression below show.

Discrete Cosine Transform Based Compression
Original picture Picture of first phase of DCT - based 
compression using 8x8 blocks
Discrete Wavelet Transform Based Compression
Original picture Picture of first phase of  DWT compression
using 3 levels and db2 wavelets

The course is aimed at juniors and seniors, though any mathematically well-prepared student will benefit from the course. The basic mathematical ideas can be built upon matrix algebra and some Fourier series. The course work will consist of homework assignments, exams and one or two projects. The primary computational tool will be Matlab. It is not necessary to know Matlab beforehand, though some computational expertise is expected (e.g. one of MATLAB, MAPLE, or C++).

This course has now been offered (at least) eight times and includes materials developed by Allen Broughton and Ed Doering several years ago, additions by Roger Lautzenheiser in Winter 01-02, and much material developed by Kurt Bryan. I have TOTALLY REVISED and REWRITTEN the notes. They are now of textbook quality and come with Matlab scripts, projects, and exercises. Our main goal will be to understand the mathematics behind the current DCT-based JPEG (see picture above) compression method and the new wavelet-based JPEG 2000 compression method (see picture above). By learning the mathematical foundations as well as their application, we expect that students will gain background to further their learning of image processing methods.

I particularly welcome any student who wants to do a related Imaging Certificate project after taking the course.

Any questions? Send me  email: kurt.bryan@rose-hulman.edu
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