Course image processing master
Responsible: Prof.Dr, Dietmar Kunz
Course
Meets requirements of following modules(MID)
Course Organization
Version |
created |
2012-01-05 |
VID |
1 |
valid from |
WS 2012/13 |
valid to |
|
|
|
Course identifiers |
Long name |
image processing master |
CID |
F07_BVA |
CEID (exam identifier) |
|
|
Contact hours per week (SWS) |
Lecture |
1 |
Exercise (unsplit) |
|
Exercise (split) |
|
Lab |
1 |
Project |
|
Seminar |
1 |
Tutorial(voluntary) |
|
|
|
Total contact hours |
Lecture |
15 |
Exercise (unsplit) |
|
Exercise (split) |
|
Lab |
15 |
Project |
|
Seminar |
15 |
Tutorial (voluntary) |
|
|
|
Max. capacity |
Exercise (unsplit) |
|
Exercise (split) |
|
Lab |
18 |
Project |
|
Seminar |
30 |
|
Total effort (hours): 150
Instruction language
Study Level
Prerequisites
Textbooks, Recommended Reading
Instructors
Supporting Scientific Staff
Transcipt Entry
Advanced Topics in Image Processing
Assessment
Total effort [hours] |
wR |
20 |
Frequency: 1/Jahr
Course components
Lecture/Exercise
Objectives
Lerninhalte (Kenntnisse)
- ill-posed problems
- regularization
- iterative methode
- mutual information
- registration of image data
Acquired Skills
Operational Competences
Additional Component Assessment
Contribution to course grade |
Frequency: 1/Jahr
Lab
Objectives
Lerninhalte (Kenntnisse)
Acquired Skills
- implement iterative image processing methds
- test image processing methods
Operational Competences
- prepare results
- summarize and present results
- assess results
Additional Component Assessment
Contribution to course grade |
fPS |
0% |
Frequency: 1/Jahr
Project
Objectives
Lerninhalte (Kenntnisse)
- reading of selected literature
Acquired Skills
- in-depth implementation and evaluation of selected image processing method
Operational Competences
- document results in an adequate way
- implement algorithim from literature
- assessment of results
Additional Component Assessment
Type |
wR |
project documentation |
Contribution to course grade |
wR |
100 % |
Frequency: 1/Jahr
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