Course detail

Computer Methods of Image Processing

FSI-9MZOAcad. year: 2023/2024

This course covers the subject of classical and digital photogtaphy, image processing and analysis by means of computer software. 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.

Language of instruction

Czech

Mode of study

Not applicable.

Guarantor

prof. RNDr. Miloslav Druckmüller, CSc.

Department

Institute of Mathematics (ÚM)

Entry knowledge

Real and complex analysis, functional analysis, basic knowledge of programming

Rules for evaluation and completion of the course

Written exam
Missed lessons can be compensated by individual consultations.

Aims

The aim of the course is to provide students with information about modern mathematical methods of image processing.


Basic knowledge of classic and digital photography, modern mathematical methods of image processing, image analysis and pattern recognition.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Pratt, W. K.: Digital Image Processing. Wiley, New York
Starck, J.L. ; Murtagh, F.; Bijaoui, A.: Image Processing and Data Analysis. Cambridge Univesity Press

Recommended reading

Druckmüller, M.; Heriban, P._: Digital Image Processing System 5.0. SOFO Brno
Klíma, M.; Bernas, M.; Hozman J.; Dvořák, P.: Zpracování obrazové informace. ČVUT Praha

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme D-ENE-P Doctoral 1 year of study, winter semester, recommended course
  • Programme D-IME-P Doctoral 1 year of study, winter semester, recommended course
  • Programme D-ENE-K Doctoral 1 year of study, winter semester, recommended course
  • Programme D-IME-K Doctoral 1 year of study, winter semester, recommended course

Type of course unit

 

Lecture

20 hod., 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

Elearning

eLearning: currently opened course