Syllabus
(2009 Spring Term)
1. Title
Digital Image Processing
2. Code
ICE626
3. Faculty
Yong Man Ro
4. Credit
3
5. Time
A.m.10:30~12:00 on Tuesday, Thursday
6. Lecture’s Overview
ICE626 Digital Image Processing
Digital image processing is a fundamental course that provides basic concept of processing of
digital image and visual contents. Students suppose to learn various idea and techniques for the
image processing, which could be applied to practical multimedia system in the Internet,
digital broadcasting and computer vision fields. Students are required to practice the algorithm
and technique learned in the lecture through consecutive experiments using computer
simulations. The verification of the algorithms is designated in the discussion session of project
conference. Students are required to develop image processing algorithms or to show the
demonstration of the assignment with a programming language like C++. General topics which
will cover in the lecture are as follows :
- Human visual perception, digitizing image (sampling and quantization)
- Image processing fundamental (enhancement and restoration)
- Image transformation and compression
- Image analysis (segmentation and recognition)
7. Textbook
A. Main book: Digital Image Processing, Rafael C. Gonzales, Richard E. Woods, AddisonWesley Publishing Company, 2nd edition
B. Reference books:
1. Digital Image Processing, K. R. Castleman, Prentice Hall, 1996
2. Digital Pictures:Representation, Compression, and Standards,
3. A. N. Netaravali and B. G. Haskell, Second Edition, Plenum, 1995
4. Two-Dimensional Signal and Image Processing, J. S. Lim, Prentice Hall PTR, 1990
5. Fundamentals of Digital Image Processing, A. K. Jain, Pretice Hall
6. Digital Picture Processing, A. Ronsenfeld and A. C. Kak, Academic Press
1
8. Exam & Evaluation (refer to rules for teaching)
Division
Credit
MidTerm
Quiz
17 %
3%
FinalTerm
Assignments
Programming
project
Homework
35 %
40%
Attendance
Total
5%
100%
10. Lecture schedule
Duration
Contents
Note
1. Introduction, class logistics, elements of
digital image processing system
2. Human visual perception
3. Sampling & quantization
1~4
week
-Homework #1: sampling
and quantization
5. Image transforms; Fourier transform
-Homework #2: FFT and
other transform
programming
6. Fast Fourier transform
-One or two Quiz
4. Relationships between pixels
7. Other separable image transforms
8. K-L transform
9. Image enhancement; point processing
10. Spatial filtering
11. Enhancement of frequency domain
-Homework #3:
implementation of image
enhancement techniques
5~8
12. Color image processing
week
13. Image restoration; degradation model
-Homework #4:
implementation of image
restoration techniques
14. Algebraic Approach
-Mid-term exam.
15. Inverse filtering
-One or Two Quiz
16. Wiener filter
9~12
17. Image compression; image redundancy
week
18. Image compression model
-Home work #5: data
redundancy
-Home work #6: lossless
2
19. Information theory
and lossy coding
20. Error-free compression
-One Quiz
21. Lossy compression
22. Compression standard
23. Applications: JPEG still-image coding;
overview
24. Continue JPEG; parameter definition
25. Continue JPEG; DCT, mode
-Home work #7: JPEG
compression
13~15
26. Image Analysis: Image featuring
week
27. Segmentation I
28. Segmentation II
-Home work #8: image
segmentation
- Final exam
Note: The above schedule could be changed
3