Image & Signal Analysis
The lecture deals with methods of signal and image analysis and reconstruction. These include, for example, frequency analysis, edge detection or the analysis of noise content. Various tools will be introduced, such as the fast Fourier transform or wavelet transform. We will also discuss the Radon transform and its application in computed tomography.
Topics:
- Fast Fourier Transformation
- Filtering signals and images
- Wavelet transformation
- Denoising of signals and images
- Quality measures for images
Some topics are covered in greater depth in the seminar “Mathematical Image Processing”.
Moodle: Link to course page
Literatur:
- K. Bredies und D. Lorenz, Mathematical Image Processing
- A. Iske, Approximation, Springer 2018
- F. Natterer, The Mathematics of Computerized Tomography, Classics in Applied Mathematics 32, SIAM, 2001