Universität Wien

050080 VU 3D Image Processing (2015W)

Continuous assessment of course work

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. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 06.10. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 13.10. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 20.10. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 27.10. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 03.11. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 10.11. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 17.11. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 24.11. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 01.12. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 15.12. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 12.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 19.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 26.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.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.

* basic image transformations, some mathematical basics
* Fourier transform
* convolution
* 3D scalar data / projection, rendering
* image restoration and reconstruction (denoising)
* vectors and tensors
* wavelets and multi-resolution

Assessment and permitted materials

Assignments: 50%
2xCourse Reflections (Reaktionsblatt): 5%
Final: 45%

Minimum requirements and assessment criteria

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

Examination topics

Reading list

Rafael C. Gonzales, Richard E. Woods Digital Image Processing 3rd edition, Addison-Wesley, 2008.

Association in the course directory

Last modified: Mo 07.09.2020 15:29