Universität Wien
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052600 VU Signal and Image Processing (2019W)

6.00 ECTS (4.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work

URL: http://vda.univie.ac.at/Teaching/SIP/
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 01.10. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 02.10. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 08.10. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 09.10. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 15.10. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 16.10. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 22.10. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 23.10. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 29.10. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 30.10. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 05.11. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 06.11. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 12.11. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 13.11. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 19.11. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 20.11. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 26.11. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 27.11. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 03.12. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 04.12. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 10.12. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 11.12. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 17.12. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 07.01. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 08.01. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 14.01. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 15.01. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 21.01. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 22.01. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Tuesday 28.01. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
  • Wednesday 29.01. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG

Information

Aims, contents and method of the course

Spatial signals are ubiquitous. Whether they are 1D signals, as in audio or time-dependent measurement/sensors, whether these are 2D photographs and LIDAR images or whether they are 3D medical volumes, climate models, or computational fluid studies; these signals are everywhere. While many of the techniques we are covering can be explained in 1D (and for didactic reasons we will fall back to 1D a number of times) there is a fundamental difference when we need to create models of processing for more-than-1D signals. While most of "image" processing is really focused on 2D images, it is important to me that we keep the 3-dimensional nature of the world we live in in mind from day one. Hence, I am presenting a course, which is mostly an image processing course, but with some topics that are necessary to properly deal with 3D images.

* linear time-invariant systems (LTI)
* Fourier transform
* sampling + convolution
* DFT + FFT
* basic image transformations, some mathematical basics
* image restoration and reconstruction (denoising)
* wavelets and multi-resolution
* 3D scalar data / projection, rendering
* vectors and tensors

Assessment and permitted materials

Assignments: 51%
2xReaction sheets: 4%
Midterm: 20%
Final: 25%

Minimum requirements and assessment criteria

Teilnahmevorraussetzungen: StEOP, PR2, MG2, THI, MOD, ADS
Empfohlene Teilnahmevoraussetzung: NUM

The grading scale for the course will be:
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%

Examination topics

The major goals of this course include:
* understanding transforms and being able to apply them to 2D images and 3D data
* understanding of implementations in Matlab
* use of rendering methods for understanding 3D data

Reading list

Rafael C. Gonzales, Richard E. Woods Digital Image Processing 4th edition, Addison-Wesley, 2018.
Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing, 3rd Edition, Pearson, 2010

Association in the course directory

Last modified: Mo 27.07.2026 10:55