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Advanced Image Analysis

Winter Term 2022

Advanced Image Analysis

Advanced Image Analysis

Lecturer: Dr. Pascal Peter
Tutor: Luisa Danalachi

Winter Term 2022

Lecture (2h) with exercises (2h)
6 credit points

Lectures: Tuesday 16-18 c.t.
First Lecture: Tuesday, October 25, 2022

Tutorials: Friday 14-16 c.t.
First Tutorial: Friday, November 11, 2022



AnnouncementsDescriptionEntrance requirementsTutorialsExams
Lecture notes/AssignmentsReferences



For detailed information at a glance, consult our welcome flyer.

7/11/2022 Registration is now closed.
20/10/2022 Registration is now open.
25/08/2022 Website is online. Registration and more detailed information will available closer to the beginning of the semester.


In this lecture, we will discuss advanced topics in the fields of image processing and computer vision. Most of the presented methods fuse the information from several images in order to produce an enhanced composite image. Examples for such techniques are super-resolution, high dynamic range (HDR) imaging, tone mapping and gradient domain techniques.

Example: Freehand High Dynamic Range Imaging
Exposure series Tone mapped HDR reconstruction without and with alignment


Requires undergraduate knowledge in mathematics (e.g. ''Mathematik für Informatiker I-III''), and elementary C knowledge. Basic knowledge in image processing and computer vision is recommendable. The lectures and tutorials will be given in English.


There are practical and theoretical weekly assignments. They will be solved in group work during tutorial sessions and written solutions will be available. Exam admission requires regular tutorial attendance. Details can be found in the introductory lecture.

If you have questions concerning the tutorials, please do not hesitate to contact Pascal Peter.


There will be two closed book written exams:

The first written exam will take place on Thursday, February 23, 2023 from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.
The second written exam will take place on Monday, April 3, 2023 from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.

You can find the detailed rules for our exams in the self test assignment in the Teams file repository.
You can participate in both exams, and the better grades counts. Please remember that you have to register online for the exam in the HISPOS system of the Saarland University.

If you cannot attend the exam, contact Pascal Peter as early as possible. In case you have proof that you cannot take part for medical reasons or you have another exam on the same day, we can offer you an oral exam as a replacement. Note that we need written proof (e.g. a certificate from a physician/Krankenschein) for the exact date of the exam.

Lecture notes / Assignments

Lecture content in the form slides and assignments are available for download via Microsoft Teams. Access will be granted after registration. In addition, you will gain access to pre-recorded videos from previous semesters. Note that the initial registration requires manual confirmation and can thus be delayed a bit.


    There is no specific book that covers the complete content of this class. Many lectures will be based on articles from journals and conferences. However, the recent book of R. Szeliski covers some of the topics and additionally summarises most of the intensively studied areas of computer vision research:
  • R. Szeliski: Computer Vision: Algorithms and Applications.
    ISBN: 978-1-84882-934-3, Springer, Berlin, 2011.
    Note: You can download a PDF version of the book here.

Further references will be given during the lecture.



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