Course detail
Digital Signal and Image Processing
FEKT-AZSOAcad. year: 2011/2012
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
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
- 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)
V. Šebesta: Signály a systémy. Skripta VUT (CS)
Recommended reading
Not applicable.
Classification of course in study plans
Type of course unit
Lecture
39 hod., optionally
Teacher / Lecturer
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)
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 hod., compulsory
Teacher / Lecturer
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.
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.