052600 VU Signal and Image Processing (2020S)
Continuous assessment of course work
Labels
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).
- Registration is open from Mo 10.02.2020 09:00 to Th 20.02.2020 09:00
- Deregistration possible until Th 30.04.2020 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 03.03. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 04.03. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 10.03. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 11.03. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 17.03. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 18.03. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 24.03. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 25.03. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 31.03. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 01.04. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 21.04. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 22.04. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 28.04. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 29.04. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 05.05. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 06.05. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 12.05. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 13.05. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 19.05. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 20.05. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 26.05. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 27.05. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Wednesday 03.06. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 09.06. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 10.06. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 16.06. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 17.06. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 23.06. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
- Wednesday 24.06. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG
- Tuesday 30.06. 15:00 - 16:30 Hörsaal 3, Währinger Straße 29 3.OG
Information
Aims, contents and method of the course
Signals with temporal or spatial structure 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. In this course, we study the mathematical foundations of signal processing and learn how to implement and apply commonly used algorithms in image analysis. Topics we cover include linear time-invariant (LTI) systems, convolution, the Fourier transform and its extensions, sampling and filtering of signals, spectral analysis, information theoretic coding and wavelet analysis.
Assessment and permitted materials
Assignments: 51%
2xReaction sheets: 4%
Midterm: 20%
Final: 25%
2xReaction sheets: 4%
Midterm: 20%
Final: 25%
Minimum requirements and assessment criteria
Prerequisites: StEOP, PR2, MG2, THI, MOD, ADS
recommended prerequesites: NUMThe 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%
recommended prerequesites: NUMThe 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 the mathematical foundations of signal processing
* being able to implement commonly used signal processing algorithms in Python
* applying signal processing algorithms to image analysis
* understanding the mathematical foundations of signal processing
* being able to implement commonly used signal processing algorithms in Python
* applying signal processing algorithms to image analysis
Reading list
1. Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing, 3rd Edition, Pearson, 2010
2. Rafael C. Gonzales, Richard E. Woods Digital Image Processing 4th edition, Addison-Wesley, 2018.
3. Donald B. Percival, Andrew T. Walden, Spectral Analysis for Physical Applications, Cambridge University Press, 1993
2. Rafael C. Gonzales, Richard E. Woods Digital Image Processing 4th edition, Addison-Wesley, 2018.
3. Donald B. Percival, Andrew T. Walden, Spectral Analysis for Physical Applications, Cambridge University Press, 1993
Association in the course directory
Module: SIP AKM IMI
Last modified: Mo 07.09.2020 15:20