EE 528: Digital Image Processing, Spring 2007

Updates

Instructor - Dr. Namrata Vaswani,   Email: namrata AT iastate.edu,   Phone: 515-294-4012,   Office: 3121 Coover Hall
Location changed: Class Location & Time:  Mon-Wed 9:30-10:50. Room: 1120 Sweeney 
Office Hours: 2-3 Friday,  11-12 Tuesday  in 3121 Coover
Prerequisites: EE 224 (Signals and Systems), EE 322 (Probability for EE), some linear algebra, calculus. EE424 is listed but not really necessary (if you know 224 and 322 well, it should suffice).

Syllabus and Class Information Sheet: pdf

Homeworks


Project Requirements, Deadlines & Topics

Extra problems (Both practical and numerical. You should now have the background to look at these problems.)

Teaching Schedule & Handouts

Handouts
See Teaching schedule for other topics covered from book
Slides on Introduction to Image Processing
Signal Processing Review notes
Image Restoration Slides
Link to KLT Tracker implementation
Edge detection, Boundary Tracing, Edge Linking
Calculus of variations
Snakes
Geometric contour repr. & Level set method
Next class: Level Set methods for segmentation


Please revise:

1. Probability for EE: EE 322 (Probability for EE) at ISU (Fall 2006)
2. Fourier Transforms (continuous and discrete), Sampling, Reconstruction, Decimation and Interpolation
a) Review notes  (updated 1/17/07).
b) An Excellent Tutorial: http://ccrma.stanford.edu/~jos/mdft/mdft.html
c) A very basic tutorial here: http://www.bores.com/courses/intro/index.htm
d)
EE 224 (Signals and Systems) at ISU (Fall 2006)
3. Linear Algebra:  http://www.maths.mq.edu.au/~wchen/lnlafolder/lnla.html (Chapters 5-10, Chap 11,12 may also be useful)


Useful Links
MATLAB Image Processing toolbox
Milan Sonka's  Image Processing notes
An excellent tutorial on DSP (DFT, sampling, decimation etc)

A useful set of Linear Algebra notes (Chap 5 and onwards)
Set of tutorials on the book page of Gonzalez and Woods'  Digital Image Processing 2/E
An easy, very basic DSP tutorial

Some Other Useful classes at ISU
EE 520 (my old Computer Vision class)
EE527 (Detection and Estimation Theory)
STAT580 (Computational Methods on Statistics)   - see for handout on Monte Carlo methods
EE524 (Digital Signal Processing)
EE523 (Random Processes)