Image Processing


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, B6, 23–25 A101, Start: 12.02.2024
  • Exercise: Tuesday, 15:30, Start: 20.02.2024

Final mark

  • Oral Exam


  • The course is open to students of the Master Business Informatics, Master Business Mathematics and Mannheim Master in Data Science (MMDS). 
  • The course is restricted to 30 participants.
  • Places are assigned on first come/first serve basis.
  • Students register for the course by email to me (keuper@uni...). If you have sent me an email and NOT received a personal reply, this means that I reserved your seat!
  • Slides and Excercises

    • provided in ILIAS
  • Requirements

    • Basic Python skills are beneficial for the exercise.
    • Basics in linear algebra are beneficial for the lecture.
  • Outline




    General Remarks & Human Visual System


    Basics of Imaging – Image Enhancement


    Image Sampling


    Noise and Basic Image Operations


    Edge Detection and Scale Pyramid Models


    Energy Minimization + Variational Optimization (1)

    20.11.2023Variational Optimization (2)  + Image Segmentation (1) (Level Sets)
    27.11.2023Image Segmentation (2) Superpixel Methods and Image Formats (remote session)
    06.11.2023Stereo Vision and Structure from Motion  – plus Q&A session
  • Literature