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Lecturer(s)
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Course content
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Lecture topics by week of the semester: 1. Signal quantization 2. Signal sampling 3. Signal aliasing 4. Fourier transform, extension to multiple dimensions, Signal spectrum, FFT 5. Signal filtering methods in the spatial/temporal and spectral domains 6. Principles of image information sensing. Analog and digital sensing elements. Analog image signal transmission 7. Principles of acoustic signal sensing 8. Sensors for the infrared region 9. Digital TV 10. Lossy and lossless compression algorithms 11. Spectrum of non-stationary signals 12. Wavelet transform 13. Wavelet transform - use for image compression The content of the exercises corresponds to the topics of the lectures.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Laboratory work
- Contact teaching
- 56 hours per semester
- Home preparation for classes
- 20 hours per semester
- Term paper
- 40 hours per semester
- Preparation for an exam
- 19 hours per semester
- Preparation for a credit (assessment)
- 15 hours per semester
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Learning outcomes
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The course provides to students essential knowledge of data transmission theory and the principles of transmission and processing of audio and video signals. The understanding of these principles is necessary for the next study of communications systems in the next semesters.
After the course will student have the knowledges from the transmission and processing of audio and video signals area. The understanding of these principles is necessary for the next study of communications systems in the next semesters.
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Prerequisites
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The basic orientation in the MATLAB environment or any of the alternative products (SCILAB, OCTAVE...). The basic digital signal processing methods (the signal discretization, the spectrum of a signal, the one dimensional Fourier transformation). The basic matrix operations (for example the matrix inversion, transposition and multiplication). The capability of problems analysis and algorithm development.
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Assessment methods and criteria
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Oral examination, Written examination, Discussion
The student attendance on all practice courses is necessitated. On the credit test the students have to present the courses knowledges. The exam is based on theoretical knowledges presented on the lectures. Students will receive exam topics at the beginning of the course. A condition for credit and examination is: 1. Submission and analysis of the term paper + theoretical discussion of the assigned problem. During the exam, understanding and approach to the problem is assessed. Comprehensiveness of the solution and independence. Authorship of the thesis is verified during the examination. 2. Presentation of a short video with descriptions/comments in EN. 3. Return of borrowed items. Semester work At the end of the semester, the student, in agreement with the teacher, chooses a suitable topic for the term paper. It is possible to use the remaining time and consult in the scheduled classes. The student may use the laboratory facilities by arrangement. Topics from previous years may be accepted only if the student demonstrates substantial completion of the topic (more than 50%) and justifies why the topic was not completed. The course of the exam The course ends with an exam, in which the student defends the term paper (presenting the procedures and describing the source code in detail) and demonstrates the knowledge gained through discussion. In case it is proved that the student is not the author of the thesis, the exam cannot be recognized and a new topic must be assigned. Furthermore, the student will create a presentation in English, which the teacher will then upload to YouTube. The presentation must include: - Name of the author of the project, Year of defence, Title of the course. - Development diagram with description of algorithms. - A sample of the function. - The presentation should not exceed 5 min. It is preferable to use subtitles instead of comments. - In the first class, students will be introduced to examples of previous presentations.
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Recommended literature
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KUMAR, N. Suresh, Arun Kumar SANGAIAH, M. ARUN a S. ANAND. Advanced Image Processing Techniques and Applications. IGI Global. Advances in Computational Intelligence and Robotics, 2017. ISBN 9781522520535.
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Prchal, J. Šimák B. Digitální zpracování signálů v telekomunikacích. Praha: ČVUT, 2001. ISBN 80-01-02149-1.
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Sanjit K Mitra. Digital Signal Processing, 4th Edition. McGraw: Hill, 2010. ISBN 978-0073380490.
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