Course detail

Digital Signal and Image Processing

FEKT-AZSOAcad. year: 2010/2011

The subject offers and introduction to the basic concepts of signals and systems, digital processing and analysis of images as an essential tool for modern biomedical engineering and bioinformatics.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. Ing. Jiří Jan, CSc.

Department

Department of Biomedical Engineering (UBMI)

Learning outcomes of the course unit

Understanding of the fundamental concepts and their relationships in the field of signal and image processing, knowledge of the fundamental application processes and their applications.

Prerequisites

successful completion of previous courses in the study area.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

requirements for successful completion of the subject: course-unit credit based on active presence in demonstration exercises, passing of final written exam.

Course curriculum

- Fundamental concepts in signals and systems, their relationships and applications
- Digital representation, digital processing and analysis of signals, presentation of selected principal methods
- Fundamentals of digital representation, processing and analysis of images, presentation of selected methods

Work placements

Not applicable.

Aims

To provide the students with understanding of the fundamental concepts and their relationships in the field of signal and image processing, presentation of the major attitudes and methods and comprehensible demonstration.

Specification of controlled education, way of implementation and compensation for absences

demonstration exercises. Attendance at lectures is recommneded (it should be compulsory, with regard to the big volume of covered learning material, difficult to comprehend without teacher´s guidance).

Recommended optional programme components

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 BTBIO-A Bachelor's

    branch A-BTB , 2. year of study, winter semester, compulsory

  • Programme EEKR-CZV lifelong learning

    branch ET-CZV , 1. year of study, winter semester, compulsory

Type of course unit

 

Lecture

39 hours, optionally

Teacher / Lecturer

prof. Ing. Jiří Jan, CSc.

Syllabus

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

13 hours, compulsory

Teacher / Lecturer

Ing. Lukáš Smital, Ph.D.
Ing. Martin Vítek, Ph.D.

Syllabus

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.