| Name des Moduls | [116290] Computational Imaging | Bezeichnung des Moduls | PAFMO129 |
| Studiengang | [128] - Physik | ECTS Punkte | 4 |
| Arbeitsaufwand für Selbststudium | 75 | Häufigkeit des Angebotes (Modulturnus) | jedes 2. Semester (ab Sommersemester) |
| Arbeitsaufwand in Präsenzstunden | 45 | Dauer des Moduls | 1 |
| Arbeitsaufwand Summe (Workload) | 120 | ||
| Modul-Verantwortliche/r | Prof. Dr. Rainer Heintzmann, Dr. Lars Lötgering |
| Voraussetzung für die Vergabe von Leistungspunkten (Prüfungsform) | project presentation (100%) |
| Zusätzliche Informationen zum Modul | A list of Literature and materials will be provided at the beginning of the semester. |
| Empfohlene Literatur | A list of Literature and materials will be provided at the beginning of the semester. |
| Unterrichtssprache | Englisch |
| Art des Moduls (Pflicht-, Wahlpflicht- oder Wahlmodul) | 128 MSc. Physics specialisation „Optics“: required elective module 628 M.Sc. Photonics: required elective module |
| Zusammensetzung des Moduls / Lehrformen (V, Ü, S, Praktikum, …) | Lecture: 2 h per week Programming Lab: 1 h per week |
| Inhalte | Review: Linear Algebra, Calculus, Python • Optimization part 1: Continuous (Euler Lagrange) and Discrete (multivariate calculus) • Programming lab: genetic algorithms + Fermat principle • Optimization part 2: nonlinear optimization, regularization, Lagrange multipliers • Optimization part 3: Convex techniques, l1 minimization • Programming lab: single pixel camera • Optimization part 4: Automatic differentiation • Matrix representation of coherent optical systems Programming lab: keras toolbox, optical eigenmodes • Multiple scattering: Born / Rytov series, beam propagation method • Tomographic inversion • Programming lab: Foldy-Lax scattering theory • Phase retrieval part 1: coherent diffraction imaging (CDI) • Phase retrieval part 2: ptychography • Programming lab: hybrid input output, shrink wrap, ptychography • Phase retrieval part 3: Fourier ptychography • Image deconvolution: structured illumination microscopy, pupil engineering • Programming lab: extended depth-of-field systems • Imaging with spatially partially coherent light • Parameter estimation: Fisher information and Cramer Rao lower bound • Programming lab: Coded aperture imaging, resolution assessment, edge responses, modulation transfer function, Fourier ring correlation • Neural networks part 1: Image classification • Neural networks part 2: Image regression • Programming lab: digit recognition, counting red blood cells |
| Lern- und Qualifikationsziele | Understanding the interplay between forward and inverse modeling in optical systems. Hands-on programming skills. |