Course detail
Digital Signal and Image Processing
FEKT-AZSOAcad. year: 2018/2019
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
Czech
Number of ECTS credits
6
Mode of study
Not applicable.
Guarantor
Learning outcomes of the course unit
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
- 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
Prerequisites
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
- basic university mathematics, including the complex integral transforms (Laplace, Fourier)
- introduction to continuous-time system theory
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. Techning methods include lectures, and computer . Course is taking advantage of e-learning (Moodle) system.
Assesment methods and criteria linked to learning outcomes
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)
- 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)
Course curriculum
1. Fundamental concepts in signal area 1 (continuous-time signal, periodical and nonperiodic, deterministic and stochastic, parameters)
2. Fundamental concepts in signal area 2 (harmonic decomposition, Fourier trasnform and spectrum)
3. Fundamental concepts in systems (I-O formulation, classification, impulse response, convolution, frequency response)
4. Digital signals 1 sampling, digital signal and its spectrum, sampling theorem, reconstruction)
5. Linear filtering 1 (principle of FIR filtering, properties and possibilities of implementation)
6. Linear filtering 2 (pronciple of IIR filtering, properties and possibilities of implementation , comparison with FIR filtering)
7. Digital signals 2 (stochastic signals, useful signal and noise, repetitive signals, complex signals)
8. Signal enhancement by averaging (fixed window and sliding window averaging, exponencial averaging)
9. Correlation and spectral analysis of signals (estimation and interpretation of correlation function, estimation and interpretation of spectrum of deterministic and stochastic signal)
10. Principles of signal representation of images (two-dimensional signal, continuous and discrete image, sampling, stochastic fields, 2D spectrum of images)
11. Representation of digital images and operators (classification of operators, basic point- and local operators)
12. Basic methods of image enhancement (transformation of brightness and colour, sharpening, noise smoothing, geometric transforms, registration and fusion)
13. Principle of image reconstruction from tomographic projections (projection, Radon transform, principle of algebraic methods)
2. Fundamental concepts in signal area 2 (harmonic decomposition, Fourier trasnform and spectrum)
3. Fundamental concepts in systems (I-O formulation, classification, impulse response, convolution, frequency response)
4. Digital signals 1 sampling, digital signal and its spectrum, sampling theorem, reconstruction)
5. Linear filtering 1 (principle of FIR filtering, properties and possibilities of implementation)
6. Linear filtering 2 (pronciple of IIR filtering, properties and possibilities of implementation , comparison with FIR filtering)
7. Digital signals 2 (stochastic signals, useful signal and noise, repetitive signals, complex signals)
8. Signal enhancement by averaging (fixed window and sliding window averaging, exponencial averaging)
9. Correlation and spectral analysis of signals (estimation and interpretation of correlation function, estimation and interpretation of spectrum of deterministic and stochastic signal)
10. Principles of signal representation of images (two-dimensional signal, continuous and discrete image, sampling, stochastic fields, 2D spectrum of images)
11. Representation of digital images and operators (classification of operators, basic point- and local operators)
12. Basic methods of image enhancement (transformation of brightness and colour, sharpening, noise smoothing, geometric transforms, registration and fusion)
13. Principle of image reconstruction from tomographic projections (projection, Radon transform, principle of algebraic methods)
Work placements
Not applicable.
Aims
- 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
- presentation of the major approaches and methods in signal and image processing and analysis
- comprehensible interpretation and demonstration of the respective practical techniques
Specification of controlled education, way of implementation and compensation for absences
Obligatory attendance at tutorials, only 20% absence may be justified by an official medical certificate.
Attendance at the lectures is only recommended.
Attendance at the lectures is only recommended.
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
26 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.