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Differential Equations in Image Processing and Computer Vision

Winter Term 2024/2025

Differential Equations in Image Processing and Computer Vision

Five Teaching Awards (4 in Computer Science, 1 in Mathematics)

Lecturer: Prof. Joachim Weickert

Assistant: Vassillen Chizhov

Winter Term 2024/2025

Lectures (4h) with theoretical and programming assignments (2h);
(9 ETCS points)

Online Lectures:
Wednesday, 10:15-12:00
Friday, 10:15-12:00

First Lecture: Wednesday, October 16

Tutorials:
Group 1 (in English): Tuesday, 14:15-16:00, E1.1 room 106.
Group 2 (in English): Tuesday, 16:15-18:00, E1.1 room 106.

First Tutorials: Tuesday, October 22

Exams:
First Exam: Friday, February 21, 14:00 - 17:00, in E1.3 HS002
Second Exam: Monday, March 31, 14:00 - 17:00, in E1.3 HS002

Many model-based techniques in image processing and computer vision make use of methods based on partial differential equations (PDEs) and variational calculus. Moreover, many classical methods may be reinterpreted as approximations of PDE-based techniques. In this course we will get an in-depth insight into these methods. For each of these techniques, we will discuss the basic ideas as well as theoretical and algorithmic aspects. Examples from medical imaging and other fields illustrate the various application possibilities. Since this class guides its participants to many research topics in our group, its attendance is required for everyone who wishes to pursue a master thesis in our group.

For registration and more detailed information, please visit the CMS.

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