Lehre und Prüfung online
Studierende in Vorlesung

Basics of image processing and image analysis - Detailseite

  • Funktionen:
  • Online Belegung noch nicht möglich oder bereits abgeschlossen
Veranstaltungsart Vorlesung Veranstaltungsnummer 3315567
Semester SoSe 2018 SWS 2
Rhythmus jedes Semester Moodle-Link  
Veranstaltungsstatus Freigegeben für Vorlesungsverzeichnis  Freigegeben  Sprache deutsch
Weitere Links LV im Stundenplan des Instituts f. Physik
Belegungsfrist Es findet keine Online-Belegung über AGNES statt!
Wichtige Änderungen Die LV findet im Sommersemester 2018 nicht statt.
Veranstaltungsformat Präsenz
Abschluss Studiengang LP Semester
Master of Science  Optical Sciences Hauptfach ( Vertiefung: kein LA; POVersion: 2015 )     1 - 10 
Master of Science  Physik Hauptfach ( POVersion: 2010 )     2 - 4 
Master of Science  Physik Hauptfach ( Vertiefung: kein LA; POVersion: 2016 )     2 - 4 
Zuordnung zu Einrichtungen
Mathematisch-Naturwissenschaftliche Fakultät, Institut für Physik
Kommentar Lern- und Qualifikationsziele
The aim is to acquaint students with the different methods available for image processing and analysis, and to give them hands-on experience in applying the theoretical concepts of the course on real-life applications in a programming project.
Prerequisites are knowledge of undergraduate level of algebra, calculus and preferably Fourier transforms and statistics. Some experience in computer programming is helpful. However the necessary tools will also be taught during the exercises.
Gliederung / Themen / Inhalte
This lecture teaches basic image processing and data analysis. During the practica we will work on programing projects that implement concepts from the theory lessons.

This is the content:

First the basics of image formation are introduced, and this will give the student a sound basis for learning about such things as:
- Nyquist sample criterion
- Linear and non-linear filters
- Background removal
- Noise statistics
- Interpolation
- ...

Then an extensive introduction to tomography follows:
- Radon transform
- Algebraic reconstruction techniques
- Reconstruction artifacts
- ...

Then it is time for processing of hyperspectral data, with a focus on principal component analysis.

Time permitting, there'll be an introduction to statistical experimental design towards the end.

Bemerkung Ansprechpartner
W. Van den Broek, Newtonstrasse 15, 3'307
Prüfung The evaluation happens through five short programming tasks that between them span the entirety of the course. Each task is approximately 100 lines of code, with an accompanying report of 2 to 5 pages. Each task accounts for 20% of the total points, and this total then determines the final grade.


Keine Einordnung ins Vorlesungsverzeichnis vorhanden. Veranstaltung ist aus dem Semester SoSe 2018. Aktuelles Semester: WiSe 2020/21.
Humboldt-Universität zu Berlin | Unter den Linden 6 | D-10099 Berlin