Course detail

Digital Signal and Image Processing

FEKT-BPC-ZSOAcad. year: 2023/2024

The subject offers an introduction to:
- basic concepts of signals and systems,
- digital signal processing and analysis,
- processing and analysis of images
as essential indispensable tools for modern biomedical engineering and bioinformatics

Language of instruction


Number of ECTS credits


Mode of study

Not applicable.

Entry knowledge

successful completion of previous courses of the respective study branch, particularly:
- basic university mathematics, including the complex integral transforms (Laplace, Fourier)
- introduction to continuous-time system theory

Rules for evaluation and completion of the course

Requirements for successful completion of the subject:
- obtaining at least 12 points (out of 24 as course-unit credit based on active presence in demonstration exercises),
- successful passing of final written exam (up to 76 points)

Obligatory attendance at tutorials, only 20% absence may be justified by an official medical certificate.
Attendance at the lectures is only recommended.


- understanding of the fundamental concepts and their relationships in the field of signal and image processing,
- presentation of the major approaches and methods in signal and image processing and analysis
- comprehensible interpretation and demonstration of the respective practical techniques

After completing the course, the student is capable of:
- interpreting the fundamental knowledge, concepts and their relationships in the field of signal and image processing,
- describing the basic methods in this area,
- describing the most important application processes and their practical use,
- choosing a proper approach and method to a given problem from this area,
- practically utilizing the chosen method in a specific computer implementation

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

J. Jan: Číslicová filtrace, analýza a restaurace signálů (2. vydání), VUTIUM (Brno) 2002 (CS)
V. Šebesta: Signály a systémy. Skripta VUT (CS)

Recommended reading

Not applicable.


Classification of course in study plans

  • Programme BPC-BTB Bachelor's, 2. year of study, winter semester, compulsory

Type of course unit



39 hours, optionally

Teacher / Lecturer


1. Fundamental concepts in the field of signals 1 (continuous signal, periodic, non-periodic, deterministic and random, parameters)
2. Fundamental concepts in the field of signals 2 (harmonic series, Fourier transform and spectrum)
3. Fundamental concepts in the field of signals (I-O description, classification, pulse response, convolution, frequency characteristics)
4. Digital signals 1 (sampling, digital signal and its spectrum, sampling theorem, reconstruction)
5. Linear filtering 1 (basics of FIR filtering, characteristics and implementation)
6. Linear filtering 2 ( basics of IIR filtering, charateristics, implementation, comparison with FIR filtering)
7. Digital signals 2 (random signals, useful signal and noise, repetitive signals, complex signals)
8. Cumulative signal processing (single and gliding cumulation, exponential cumulation)
9. Correlation and frequency signal analysis (estimation and interpretation of the correlation function, estimation and interpretation of the spectrum of deterministic and random signal)
10. Basics of signal representation of images (two-dimensional signals, continuous and discrete images, sampling, random fields, two-dimensional image spectrum)
11. Representation of digital images and operators (classification of operators, basic point and local operators)
12. Fundamental methods of image modification (transformation of brightness and colours, zooming, noise smoothing, geometric transformations, adjusting and fusion)
13. The principles of tomographic projection reconstruction (projection, Radon transformation, the principle of algebraic methods, the method of spectral sections, filtred back projection)

Exercise in computer lab

26 hours, compulsory

Teacher / Lecturer


1. Examples of signals, harmonic synthesis, random signals. Experimental acquisition of speech signals. Spectra of deterministic and random signals.
2. Signal passing through the system, frequency and pulse characteristics, signal adjustment, signal digitization, sampling theorem application, aliasing.
3. Examples of FIR and IIR filters, comparison of characteristics, verification of effects on individual signals
4. Cumulative processing of repetitive signals, comparison of approaches.
5. Correlation analysis of random signals. Spectral analysis of (experimentally scanned) deterministic and random signals.
6. Examples of digital images (resolution, dynamics, colour) experimental digital image acquisition, application of highlighting operators. Demonstration of tomographic reconstructions.