|
| Udgave: |
Efterår 2012 NAT |
| Point: |
7,5 |
| Blokstruktur: |
1. blok |
| Skemagruppe: |
C |
| Fagområde: |
dat |
| Varighed: |
Full quarter |
| Omfang: |
About 20 hours of course activity per week. |
| Studieordning: |
Computer Science Master |
| Uddannelsesdel: |
Kandidat niveau |
| Kontaktpersoner: |
Francois Lauze, francois@diku.dk |
| Andre undervisere: |
Sami Brandt, sbrandt@diku.dk |
| Skema- oplysninger: |
 Vis skema for kurset
Samlet oversigt over tid og sted for alle kurser inden for Lektionsplan for Det Naturvidenskabelige Fakultet Efterår 2012 NAT |
| Undervisnings- form: |
The course will be a mixture of lectures, pen-and-paper exercises and programming exercises in e.g. Matlab |
| Formål: |
The purpose of this course is to give the student working knowledge of common pre-processing algorithms on data sampled on a regular grid, with special emphasis on how basic concepts from continuous analysis are used as data models, and how these may be implemented numerically. |
| Indhold: |
This course is about transformation and analysis of sampled data. Methods and examples are drawn from applications on 1D signals and 2D images. The tools learned are common first steps in any application involving sampled data. Topics to be covered are:
- Signal and image processing fundamentals
- Sampling, Sampling theorem, Fourier transform
- Convolution, linear and non-linear filtering
- Image transforms
- Image restoration, inverse filtering
- Image segmentation and feature extraction
- Representation, and description
- Data compression
|
| Målbeskrivelse: |
To get maximum grade the student must successfully be able to:
- Know and apply the theoretical basics of digital signal and image processing
- Implement filters in the frequency and spatial domain.
- Implement algorithms for pre-processing of images and evaluate the result.
- Analyze and highlight the relevant content of images by using image transforms.
- Understand the principles and design filters for image restoration.
- Write programs that extract features such as edges and regions.
- Know and apply elementary representation methods in description of image content
- Know and apply the principles of image compression methods
|
| Tilmelding: |
Via KUnet from May 15th to June 1st. |
| Faglige forudsætninger: |
None. |
| Formelle krav: |
None. |
| Eksamensform: |
Continuous evaluation of written assignments evaluated using internal grading and the 7-point grading scale.
Re-exam: oral examination (25 minutes including grading) in course curriculum without preparation. Internal grading using the 7-point grading scale.
|
| Eksamen: |
Løbende evaluering.
Reeksamen: Mundtlig prøve den 30. januar 2013.
|
| Kursus hjemmeside: |
 |
| Undervisnings- sprog: |
Kun engelsk
|
| Sidst redigeret: |
9/8-2012 |