Module Number MEINFM3143 |
Module Title Image Processing |
Type of Module Compulsory |
---|---|---|
ECTS | 6 | |
Work load - Contact time - Self study |
Workload:
180 h Class time:
60 h / 4 SWS Self study:
120 h |
|
Duration | 1 Semester | |
Frequency | In the winter semester | |
Language of instruction | German and English | |
Type of Exam | Written Test |
|
Lecture type(s) | Lecture, Tutorial | |
Content | Covered topics include: Fourier series, Fourier transform, properties of the Fourier transform, discrete Fourier transform, sampling and aliasing, linear operations, PSF, LSI systems, FIR and IIR filters, image reconstruction (Wiener filter), multiscale representation, wavelets, edge detection, segmentation, image mapping, cross-correlation, morphological operations. |
|
Objectives | The students know the mathematical basics of image processing and know which algorithms exist for the basic tasks in image processing and how they are applied. In the exercises, the students have learned to apply their theoretical knowledge to solve concrete problems in image processing and to implement appropriate implement the corresponding algorithms. |
|
Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Lecture
V
o
3
4.5
wt
90
g
100
Tutorial
Ü
o
1
1.5
|
|
Prerequisite for participation |
INFM1010 Mathematics for Computer Science 1: Analysis, INFM1020 Mathematics for Computer Science 2: Linear Algebra, INFM1110 Practical Computer Science 1: Declarative Programming, INFM1120 Practical Computer Science 2: Imperative and Object-Oriented Programming |
|
Lecturer / Other | Schilling | |
Literature | Es soll entweder (INFM1110 oder INFM1120) und (INFM1010 oder INFM1020) bestanden worden sein. |
|
Last offered | Wintersemester 2022 | |
Planned for | Wintersemester 2024 | |
Assigned Study Areas | BIOINFM2510, INFM2510, INFM3110, MDZINFM2510, MEINFM |