Presentation of the basic concepts of digital image processing,
from image acquisition, digitization, and preprocessing, to image
enhancement, restoration, segmentation and description. Both standard linear
image processing algorithms are treated, as well as some concepts and
algorithms from nonlinear morphological image processing. Also, some recent
results on multiscale image analysis are presented. The course aims at
fostering insight in the theoretical (mathematical) background needed for
modeling image formation, image errors and noise sources and developing
correction methods. Also, there is strong emphasis on design and
implementation of image processing algorithms. The course provides the
necessary knowledge for further study in Computer Vision, Scientific
Visualization and Image Pattern Recognition.
For students with deficiencies in mathematical background, additional meetings with the teacher can be organized upon request.
Lectures (7 weeks, 2h p.w.), obligatory practicals. The practicals consist of a number of sessions with assignments. Study load: lectures+lab sessions+self study: 14h p.w. (total 140h).
The following materials are needed:
During each course week a number of lab sessions with assignments has to be completed, and reported about. The lab sessions have to carried out in pairs. Lab instructor is Michel Westenberg (BB-490, email: firstname.lastname@example.org), whom you can consult, preferably by email, if you have questions about the lab sessions.
Each student needs an account (csg-number) on our student computer system. If you don't yet have a csg-number, you can inform the lab instructor about it, who will then arrange an account for you with the system administrator.
Of each lab session, a report has to handed in within two weeks, containing (i) answers
to the questions, (ii) source code of programs you wrote (iii) images (with
captions) of results.
Reports/source code has to be handed in to the lab instructor (see Nestor for details).
A selection of books on image processing.
A selection of web links on Image Processing and software.
To earn the credits for the course, you have to comply with the following:
The final score is determined as follows:
(2*written-test-score + lab-sessions-score)/3.
You can only pass when the scores for the written test and the lab sessions are both >=5.
Jos B.T.M. Roerdink, Johann Bernoulli Institute for Mathematics and Computer Science, RuG, JBI-480, tel. 363 3931.