The majority of scientific and technical applications require the extraction of desired information from previously recorded measured values. Classical examples of this are imaging techniques such as computed tomography, which provide non-invasive information about the inside of a patient or workpiece.
From a mathematical point of view, this process is the solution of an inverse problem and requires careful modelling and analysis of the problem as well as the development of suitable numerical solution methods, which must ensure a balance between accuracy and data error. One approach is the formulation of suitable optimization problems, which are solved by adding problem-adapted penalty terms.
News for Students
- Summer Term Courses SS22
lectuer and exercise: Grundlagen inverser Probleme - WinterTerm Courses WS21/22
Lecture: Introduction to Optimization (Einführung in die Optimierung) and Mastersemiar Moderne Herausforderungen in Bildverarbeitung und Bildgebung - IMNG-OIP BMBF project iDeLIVER: Innovation Lab
call for applications - Summer Term Courses SS21
Lecture: Mathematical Image Processing (Mathematische Methoden der Bildverarbeitung) and Seminar: Optimization and Inverse Problems - Summer Term Courses SS20
Lecture: Regularisation of inverse problems and seminar: Sparsity and compressed sensing
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Bernadette Hahn-Rigaud
Prof. Dr.Chairholder OIP
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- Prof. Bernadette Hahn-Rigaud
Carola Stahl
Administration
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