Module MA5032 T

Duration

1 Semester

Turnus of offer

every second summer semester

Credit points

4

Course of studies, specific fields and terms:

• Master Biophysics 2023, module part, advanced curriculum
• Master MES 2020, module part, mathematics / natural sciences
• Master Biophysics 2019, module part, advanced curriculum
• Master MES 2014, module part, mathematics / natural sciences

Classes and lectures:

• Numerical Methods for Image Computing (exercise, 1 SWS)
• Numerical Methods for Image Computing (lecture, 2 SWS)

Workload:

• 10 hours exam preparation
• 45 hours in-classroom work
• 65 hours private studies and exercises

Contents of teaching:

• Imaging process an imaging modalities
• Grids and image representation
• Operators in spatial and frequency domain
• Discrete Fourier Transform/FFT und Anwendungen
• JPEG
• Poisson equation and finite differences discretization
• Splitting methods
• Multigrid methods

Qualification-goals/Competencies:

• The students are familiar with fundamental numerical concepts in image computing.
• They have experience in realizing practical solutions.
• They can implement numerical algorithms on a computer.
• They understand selected methods for solving large linear systems.
• They can implement selected methods for solving large linear systems.
• Interdisciplinary qualifications:
• Students have advanced skills in modeling.
• They can translate theoretical concepts into practical solutions.
• They are experienced in implementation.
• They can think abstractly about practical problems.

Grading through:

• exam type depends on main module

Responsible for this module:

• Siehe Hauptmodul

Teacher:

• Institute of Mathematics and Image Computing
• Prof. Dr. rer. nat. Jan Modersitzki
• Prof. Dr. rer. nat. Jan Lellmann

Language:

• German and English skills required

Notes:

Last Updated:

14.12.2021