Prof. Michel Kocher, HEIG-Vd, Switzerland

In this course 2 major approaches of image processing will be developed.

First, the linear approach based on the Signal Processing theory. This methodology is based on linear models, convolution, Fourier transform, correlation and filter design.

Second, a non-linear approach provided by the Mathematical Morphology framework. This paradigm, developed in France about 50 years ago only used minimum and maximum operators as well as intersection, union and negation. It produces astonishing good results, very robust to noise and is, in certain cases a very interesting alternative to the linear approach.

These 2 methodologies will be described in theory and with numerous applications taken from the industrial world as well as from the biomedical domain. The students will apply the described algorithms by the help of the Matlab language and the Image Processing toolbox. At the end of the course, the students will be able to describe an image processing problem in term of different algorithms. They will also be able to program some of them and to compare them in term of speed performance (complexity) and noise robustness.

Students

Michael Bertapelli
Tiffany Silva
Swati Singhi
Mitchel Vlentina Dsouza
Manoj Hosabettu Rao
John Blanche
Babak Goshtasbi 
Haney Williams
Sarah Wannamaker
Michael Haney
Andrew McCandless
Edwards Reyes
Brandon Bass
Alexandre Kovar
Cyprien Huissoud
Arnaud Burkhalter
Steve Lienhard
Lionel Gaillard