Image processing in Physics 1
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
PH2138 is a semester module in English language at Master’s level which is offered in winter semester.
This module description is valid to SS 2013.
If not stated otherwise for export to a non-physics program the student workload is given in the following table.
|Total workload||Contact hours||Credits (ECTS)|
|150 h||60 h||5 CP|
Responsible coordinator of the module PH2138 is Franz Pfeiffer.
Content, Learning Outcome and Preconditions
Image processing and reconstruction techniques
How to make nice images in physics
This course will cover a wide range of advanced techniques used for image processing and image reconstruction, with a special focus on physical science applications. Following a problem-solving philosophy, the course will motivate all techniques and fundamental concepts with problems drawn from real-life applications.
After participation to the Module, the student:
1. Will know the fundamentals of numerical analysis.
2. Will know the basics of the standard imaging analysis methods in research and the industry.
3. Will have an overview of the state of the art in many fields of imaging physics.
4. Is able to solve typical data analysis problems occurring in experimental physics and engineering.
No specific computer science knowledge is required. The practicals offered together with the course also do not require any specific knowledge.
Some basic mathematics knowledge is expected: this includes Fourier Transformation, Basis Statistics, Linear Algebra (Matrix). In general the mathematical content will not be the focus of the course.
Courses, Learning and Teaching Methods and Literature
Learning and Teaching Methods
Each class will address a specific technique, yet all will be linked by recurrent essential topics including Fourier analysis, linear algebra, iterative techniques, maximum likelihood and convex optimization.
Together with each class, an exercise lesson is offered, where the student can directly apply and test the studied method. Typically this will involve writing a few lines of code (<10) to complete an existing program.
Description of exams and course work
In an oral exam the learning outcome is tested using comprehension questions and sample problems.
In accordance with §12 (8) APSO the exam can be done as a written test. In this case the time duration is 60 minutes.
Remarks on associated module exams
The exam for this module can be taken together with the exam to the associated follow-up module PH2147: Image Processing in Physics 2 / Bildverarbeitung in der Physik 2 after the follwoing semester. In this case you need to register for both exams in the following semester.
The exam may be repeated at the end of the semester. There is a possibility to take the exam in the following semester.