Computer Methods of Image Processing (FSI-9MZO)

Academic year 2017/2018
Supervisor: prof. RNDr. Miloslav Druckmüller, CSc.  
Supervising institute: ÚM all courses guaranted by this institute
Teaching language: Czech or English
Aims of the course unit:
The aim of the course is to provide students with information about modern mathematical method of image processing.
Learning outcomes and competences:
Basic knowledge of classic and digital photography, modern mathematical methods of image processing, image analysis and pattern recognition.
Real and complex analysis, functional analysis, basic knowledge of programming
Course contents:
This course covers the subject of classical and digital photogtaphy, image processing and analysis by means of computer. The course familiarises PhD students with the digital image processing theory and selected topics of image analysis. It focuses on digital images representation and reconstruction, filtration in frequency and spatial domain, noise analysis and filtration, image enhancement, image segmentation, objects analysis and recognition, analysis of multi-spectral images.
Teaching methods and criteria:
The course is taught through lectures explaining the basic principles and theory of the discipline.
Assesment methods and criteria linked to learning outcomes:
Written exam
Controlled participation in lessons:
Missed lessons can be compensated by individual consultations.
Type of course unit:
    Lecture  10 × 2 hrs. optionally                  
Course curriculum:
    Lecture 1. Principles of classic and digital photography
2. Numeric image representation, graphics formats, image data compression
3. Images reconstruction, statistical image characteristics
4. Pixel values transforms
5. Convolution, space domain filtration
6. Fourier transform, frequency domain filtration
7. Low-pass and high-pass filters, nonlinear filters
8. Adaptive filters
9. Additive noise - analysis and filtration
10. Impulse noise - analysis and filtration
11. Image segmentation
12. Object analysis
13. Pattern recognition and object classification

Literature - fundamental:
1. Pratt, W. K.: Digital Image Processing. Wiley, New York
2. Starck, J.L. ; Murtagh, F.; Bijaoui, A.: Image Processing and Data Analysis. Cambridge Univesity Press
Literature - recommended:
1. Klíma, M.; Bernas, M.; Hozman J.; Dvořák, P.: Zpracování obrazové informace. ČVUT Praha
2. Druckmüller, M.; Heriban, P._: Digital Image Processing System 5.0. SOFO Brno
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester