052600 VU Signal and Image Processing (2021W)
- Registration is open from Mo 13.09.2021 09:00 to Mo 20.09.2021 09:00
- Deregistration possible until Th 14.10.2021 23:59
Classes (iCal) - next class is marked with N
We will adopt a mixed / hybrid format that complements pre-recorded video lectures with in-person review sessions in the lecture hall. New video lectures and tutorials will be made available on Moodle on an ongoing basis, typically on Fridays. These videos form the basis for the review sessions, which will be held in-person in the lecture hall and simultaneously streamed on Moodle via Collaborate sessions. In the review sessions, we will review the most important concepts introduced in the videos and answer any questions you may have. Attendance of the review sessions is not mandatory but *strongly recommended* to understand the material at a depth that is required for passing the course.Attendance of each review session in person in the lecture hall is limited to 30 students on a first-come-first-serve basis. The 3G rule applies, i.e., you must have a valid negative COVID test, a valid vaccination, or a certificate of recovery to be admitted into the lecture hall.
Aims, contents and method of the course
Assessment and permitted materials
* Two feedback sheets: 4%
* Midterm: 20%
* Final: 25%In addition, you can earn up to 10% of bonus points by answering questions on Moodle about the pre-recorded videos prior to each review session.
Minimum requirements and assessment criteria
Recommended prerequisites: NUMGrading will be done according to the following scheme:1. At least 87.5%
2. At least 75.0%
3. At least 62.5%
4. At least 50.0%In addition, you need at least 10% of the points on each assignment and on each exam to pass the course.
* Understanding the theory of signals and linear time-invariant systems.
* Becoming familiar with spectral transformations and data compression algorithms.
* Being able to implement common transformations in Python and applying them to time-series and images.
2. Donald B. Percival, Andrew T. Walden, Spectral Analysis for Physical Applications, Cambridge University Press, 1993
3. Rafael C. Gonzales, Richard E. Woods Digital Image Processing 4th edition, Addison-Wesley, 2018.
4. Boaz Porat, Digital Processing of Random Signals, Dover Publications, 2008.