ECE 901 
 
Special Topics in Communications: 
Advanced Image and Video Processing 
 
 
3 Credits 
 
Spring 1998
Course Summary

Instructor: Professor Damon Tull

Schedule: T/R - 9:30am-10:45pm
 
Course objectives:  To introduce and explore in detail recent developments and applications in digital image and video processing. This course is oriented towards graduate students seeking a "hands-on" exposure to advanced research areas in the field.

Text: Selected articles will be put on reserve.

Topics covered:

Image formation  Motion estimation Robust regularization
Degradation models  Block matching  Robust iterative algorithms
Regularization theory Optical flow Robust regularized restoration
Iterative image restoration Robust statistical procedures Robust motion estimation
 
Prerequisites: Digital signal processing (ECE 431 or equiv.), linear algebra (MATH 340 or equiv.), introductory probability (ECE 430 or equiv.), computer programming experience and familiarity with World Wide Web required.  Image Processing (ECE 533 or equiv.), strongly recommended.

Registration:  Graduate students only.

Course activities:
Class participation:
Interactive discussion based on assigned articles.
Homework:
Computer implementations, (5) total.  Assignments will be based on lecture and articles discussed in class.  C, Matlab, IDL are acceptable, additional languages are subject to approval.
Final Project:
Simulation, paper and oral presentation.

Evaluation criteria:
Class participation (10%):
Individual students will lead discussion on selected articles.
Homework (50%):
Grade based on results and written analysis of topic and approach.
Final project  (40%):
Should be a significant extrapolation of a topic discussed in course. Additional simulations are required to illustrate results.  A (journal styled) paper and 12 minute oral presentation describing results and methods are required.  Project topics must be pre-approved by instructor.