1. ECE 533 Digital Image Processing

2. Outline Course homepage: Course descriptions Outlines Course conduct
Course descriptions
Outlines
Course conduct
(c) by Yu Hen Hu

3. Course Description Goals: Pre-requisites
Understand 2D signal processing theory
Familiar with basic image processing techniques: filtering, restoration, coding
Exposure to some advanced topics: segmentation, etc.
Pre-requisites
linear signals and systems,
1-D Fourier Transform,
basic linear algebra,
basic probability theory and
basic programming techniques.
Knowledge of ECE431 Digital Signal Processing is desirable.
(c) by Yu Hen Hu

4. Course Description Optional Discussion Office hours Textbook:
Used for teaching Matlab image processing box and perhaps other software
Schedule will be announced separately
Office hours
TBA
Textbook:
Digital Image Processing R. C. Gonzalez and R. E. Woods Addison-Wesley Pub. Co., New York, (2nd edition) 2002
Text book website:
(c) by Yu Hen Hu

5. Course Description Computer Usage: Grading policy:
Mainly using Matlab with image processing toolbox.
Project may require use of scanner or digital camera. If so, instruction of proper usage will be provided.
Grading policy:
15 % Five to six homework assignments
40 % Two Midterm examinations
30 % Final Examination
15 % Project
(c) by Yu Hen Hu

6. Course Outline Tentative plan, will be updated from time to time.
Exam Dates (firm):
9/30, R, in-class, midterm #1
10/28, R, in-class, midterm #2
12/17, F, 2:45-4:45 pm, final exam.
All in 1610 Engr. Hall
Homeworks due in class.
Some homework problems may require posting on your own web page. So each student should prepare a web page on his/her CAE unix account.
(c) by Yu Hen Hu

7. Project
Team project:
2-person team work on a project.
3-person or more in a team would require instructor approval
A list of potential project topics will be suggested. Students may also propose their own project topics subject to approval.
A written project proposal and report must be submitted.
Power-point project presentation is also required.
Project is graded on:
Difficulty/complexity
Originality/creativity
Completeness, presentation, etc.
(c) by Yu Hen Hu

8. Course conduct You must do the homework on your own!
Copying other’s homework or exam papers is a serious offense of academic misconduct and will be pursued according to university rules
If you have conflict with exam hours, inform your instructor at least two weeks before the exam to discuss possible alternatives.
Final examination date and time can not be changed unless direct conflict with other finals.
(c) by Yu Hen Hu

9. Course Plan Introduction Human visual system Image enhancement
Motivation,
Review of mathematics and theories
Human visual system
Vision
Color
Image enhancement
Point based
Filtering
transformation
Image restoration
Degradation model
Inverse filtering
Constrained optimization
Image coding
Transform coding
Video coding
Image analysis
Edge detection
Segmentation
representation
(c) by Yu Hen Hu