SubjectsSubjects(version: 955)
Course, academic year 2019/2020
Digital Signal and Image Processing - S445016
Title: Digital Signal and Image Processing
Guaranteed by: Department of Computing and Control Engineering (445)
Faculty: Faculty of Chemical Engineering
Actual: from 2012 to 2019
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:2/2, Ex [HT]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: English
Teaching methods: full-time
Teaching methods: full-time
Additional information:
Guarantor: Procházka Aleš prof. Ing. CSc.
Examination dates   Schedule   
The subject includes general methods of analysis and processing of sequences of observed signals and images ( Fundamental mathematical methods include discrete Fourier transform for analysis of multidimensional signals, z-transform for system description, selected statistical and numerical methods including the use of difference equations for the time-domain system description and design of digital filters. Algoritmic methods are implemented in the MATLAB and Simulink environment using both numerical methods and symbolic mathematics. Projects include the application of selected methods for biomedical signal and image analysis, environmental signal processing and energy data prediction.
Last update: Procházka Aleš (04.07.2012)

[1] T. Bose: Digital Signal and Image Processing, Wiley, 2004

[2] Vaseghi S.V.: Multimedia Signal Processing, Wiley, 2007.


Last update: Procházka Aleš (04.07.2012)
Requirements to the exam

In the frame of computational laboratories it is necessary to evaluate 3 projects including mathematical analysis of methods used and their verification in the MATLAB/Simulink environment. During exam the knowledge of mathematical metods of signal and image analysis and processing is verified together with their algorithmic implementation (

Last update: Procházka Aleš (04.07.2012)

1. Algorithmic tools of digital signal processing, fundamentals of MATLAB environment

2. Numerical, symbolic and visualization tools of MATLAB, data files processing

3. Time-domain signal representation, difference equations, selected statistical methods

4. Frequency-domain signal analysis, sampling, discrete Fourier transform, decomposition

5. Spectrum estimation, aliasing, short-time Fourier transform, window functions

6. Z-transform and system description, discrete transfer function, frequency transfer function

7. Digital filters, basic methods in the time domain, convolution, FIR filters, filter banks

8. IIR filters, basic properties, signal decimation

9. Filtering methods in frequency domain, signal reconstruction, window functions

10. Linear methods of time series modelling and prediction, SVD a QR algorthm, model selection

11. Nonlinear methods of signal processing, median filters, principles of neural networks

12. Basic methods of image analysis, 2D Fourier transform, image processing

13. Signal processing in engineering, signal prediction, Simulink environment, basic blocks

14. Biomedical signal and image processing

Last update: Procházka Aleš (04.07.2012)