Image Processing
Contents
In this course, we teach the fundamentals of image processing, starting from the human visual system and the basics of digital image acquisition. The goal is to understand the technical and theoretical basis of image processing and to be able to implement basic algorithms in practice.
Time and Location
- Lecture: Monday, 13:45, A5, C0.13 , Start: 09.02.2026
- Exercise: Tuesday, 15:30, A5, C0.13, Start: 17.02.2026
Instructor
- Lecture: Prof. Dr.-Ing. Margret Keuper
- Exercise: Katharina Prasse
Final mark
- written examination (90 minutes)
Participation
- The course is open to students of the Master Business Informatics, Master Business Mathematics and Mannheim Master in Data Science (MMDS).
- We invite you to join the ILIAS course already.
Slides and Excercises
- provided in ILIAS
Requirements
- Basic Python skills are beneficial for the exercise.
- Linear algebra is beneficial for the lecture.
Outline
Week Topic 09.02.2026 General remarks & human visual system 16.02.2026 Basics of imaging & image enhancement 23.02.2026 Image sampling 02.03.2026 Noise and basic image operations 09.03.2026 Image denoising 16.03.2026 Edge detection, scale pyramid models & wavelets 23.03.2026 Energy minimization 30.03.2026 Easter break 06.04.2026 Easter break 13.04.2026 Image formats & variational optimization (1) 20.04.2026 Variational optimization (2)
27.04.2026 Image segmentation (1) (level sets) 04.05.2026 Image segmentation (2) 11.05.2026 Stereo Vision 18.05.2026 Structure from motion 25.05.2026 Q&A session Literature
- R. Szeliski: Computer Vision Algorithms and Applications, Springer, 2010. ISBN: 978-1-84882-934-3. (Online available: http://szeliski.org/Book/)
- Forsyth, J. Ponce: Computer Vision: A Modern Approach, Prentice Hall, 2nd edition, 2012. ISBN: 978-0136085928 (Online available: cmuems.com/excap/readings/forsyth-ponce-computer-vision-a-modern-approach.pdf)