Course detail
Processing of multidimensional signals
FEKT-BPC-ZVSAcad. year: 2023/2024
The Processing of Multidimensional Signals course addresses one-dimensional time signals and two-dimensional image signals as well. Computer based methods and procedures intended for signal and image processing are the main parts of the course.
Language of instruction
Czech
Number of ECTS credits
6
Mode of study
Not applicable.
Guarantor
Entry knowledge
The basic knowledge on the level of secondary school is required in the Processing of Multidimensional Signals course.
Rules for evaluation and completion of the course
Weekly computer exercises (40 pts) and a final exam (60 pts) are evaluated during the Processing of Multidimensional Signals course. For successful pass the course, obtaining of at least half of available points is required in both mentioned parts.
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
Aims
The course is divided into two parts: discrete signals and discrete images. First of all, fundamentals of signal processing, sampling theory, signal reconstruction and discrete filters are introduced with a view to further image processing. Second part of the course contains theory of discrete image processing as geometric and brightness transformations, integral transformations, gradient operators, mathematical morphology and fundamentals of segmentation and classification.
Graduate of the course is able to design and to implement algorithms and methods for processing of both one-dimensional time signals and two-dimensional image signals.
Graduate of the course is able to design and to implement algorithms and methods for processing of both one-dimensional time signals and two-dimensional image signals.
Study aids
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
Gonzalez, R.C. & Woods, R.E., Digital image processing. 4th ed., Upper Saddle River: Prentice-Hall, 2017, ISBN 1292223049 (CS)
Hlaváč V., Šonka M.: Počítačové vidění. Grada 1992. ISBN 80-85424-67-3. (CS)
Hlaváč V., Šonka M.: Počítačové vidění. Grada 1992. ISBN 80-85424-67-3. (CS)
Recommended reading
Russ J.C.: The Image Processing Handbook. CRC Press 1995. ISBN 0-8493-2516-1. (EN)
Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)
Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)
Elearning
eLearning: currently opened course
Classification of course in study plans
- Programme BPC-AMT Bachelor's 3 year of study, summer semester, compulsory
Type of course unit
Lecture
26 hod., optionally
Teacher / Lecturer
Syllabus
1. Introduction to signal processing.
2. Introduction to image processing.
3. Discrete image.
4. Image representation and properties.
5. Brightness transformations.
6. Geometrical transformations.
7. Noise filtration.
8. Edge and corner detection.
9. Integral transform I.
10. Integral transform II.
11. Mathematical morphology.
12. Colour models.
13. Image files formats.
2. Introduction to image processing.
3. Discrete image.
4. Image representation and properties.
5. Brightness transformations.
6. Geometrical transformations.
7. Noise filtration.
8. Edge and corner detection.
9. Integral transform I.
10. Integral transform II.
11. Mathematical morphology.
12. Colour models.
13. Image files formats.
Laboratory exercise
39 hod., compulsory
Teacher / Lecturer
Syllabus
Practical practice of the material from the lecture
- Using MATLAB in image processing
- Discrete signals
- Discrete images
- Arithmetic operations
- Brightness transformations
- Geometric transformations
- Discrete convolution
- Linear and non-linear filtering
- Edge detection
- Filtering in the frequency domain
- Morphological operations
- Signal processing examples
Elearning
eLearning: currently opened course