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Course detail

Computer Methods of Image Processing

Course unit code: FSI-9MZO
Academic year: 2016/2017
Year of study: Not applicable.
Semester: winter
Number of ECTS credits:
Learning outcomes of the course unit:
Basic knowledge of classic and digital photography, modern mathematical methods of image processing, image analysis and pattern recognition.
Mode of delivery:
Not applicable.
Real and complex analysis, functional analysis, basic knowledge of programming
Not applicable.
Recommended optional programme components:
Not applicable.
Course contents (annotation):
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.
Recommended or required reading:
Klíma, M.; Bernas, M.; Hozman J.; Dvořák, P.: Zpracování obrazové informace. ČVUT Praha
Pratt, W. K.: Digital Image Processing. Wiley, New York
Druckmüller, M.; Heriban, P._: Digital Image Processing System 5.0. SOFO Brno
Starck, J.L. ; Murtagh, F.; Bijaoui, A.: Image Processing and Data Analysis. Cambridge Univesity Press
Planned learning activities and teaching methods:
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
Language of instruction:
Czech, English
Work placements:
Not applicable.
Course curriculum:
Not applicable.
The aim of the course is to provide students with information about modern mathematical method of image processing.
Specification of controlled education, way of implementation and compensation for absences:
Missed lessons can be compensated by individual consultations.

Type of course unit:

Lecture: 20 hours, optionally
Teacher / Lecturer: prof. RNDr. Miloslav Druckmüller, CSc.
Syllabus: 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

The study programmes with the given course