Compression of images and signals
| Code | Completion | Credits | Range | Language |
|---|---|---|---|---|
| B2M37KASA | Z,ZK | 6 | 2P+2C | Czech |
- Garant předmětu:
- Stanislav Vítek
- Lecturer:
- Karel Fliegel, František Rund, Václav Vencovský, Stanislav Vítek
- Tutor:
- Karel Fliegel, František Rund, Václav Vencovský, Stanislav Vítek
- Supervisor:
- Department of Radioelectronics
- Synopsis:
-
The subject deals with compression methods and techniques. Main goal is to introduce basic concepts of lossless and lossy compresion of audiovisual information (entropy, redundancy and irrelevancy). Within the laboratory exercises students will work with implementations of particular algorithms, including objective and subjective methods of quality evaluation.
- Requirements:
-
Basic methods and techniques of acquiring, transmission, processing and reproduction of audiovisual signals.
- Syllabus of lectures:
-
1. Introduction, theory of information, entropy. Shannon-Fann coding, Huffman coding.
2. Adaptive Huffman coding, Lempel-Ziv-Welch algorithm.
3. QM coder, PPM data compression scheme.
4. Scalar quantization, optimized scalar quantization, vector quantization.
5. Human hearing, data reduction - masking, binaural hearing. Evaluation of audio quality.
6. Lossless and lossy audio compression. Filter banks, psychoacoustic model, quantization, coding, joint stereo.
7. Audio coding standards (ATRAC, Ogg Vorbis, MPEG1, MPEG2, MPEG4, MPEG7, AC3, ...).
8. Human visual system, data reduction. Evaluation of visual information quality.
9. Compression of still images, JPEG, JPEG-2000.
10. Video compression techniques: motion vector, pre & postprocessing.
11. Video coding standards, MPEG1, MPEG2, H.264/AVC, H.265/HEVC.
12. Streaming in communication networks.
13. Mobile multimedia computing. Digital content protection, watermarking.
14. New directions in audiovisual information conding, multiview coding.
- Syllabus of tutorials:
-
1. Introduction, signal and image processing in Matlab.
2. Analysis of the characteristics of signals, the arithmetic coder.
3. Huffman coding.
4. VQ encoder. Projects assignment.
5. Implementation of simple lossy audio encoder in Matlab.
6. Subjective and objective evaluation of the quality of the compressed audio signal.
7. Compression of still pictures according to standard JPEG and JPEG-2000.
8. Principles lossy video compression, motion vector, MPEG standards.
9. subjective and objective evaluation of the quality of the compressed video signal.
10. Watermarking.
11. Work on semester project.
12. Work on semester project.
13. Presentation of semester projects.
14. Test, assessment.
- Study Objective:
-
Main goal is to introduce basic concepts of lossless and lossy compresion of audiovisual information (entropy, redundancy and irrelevancy).
- Study materials:
-
[1] Proakis J.: Digital signal processing, Harlow, 2014, ISBN: 978-1-29202-573-5
[2] Thyagarajan, K. S.: Still Image and Video Compression with MATLAB, Willey, 2011, ISBN: 978-0-470-88692-2
[3] Sayood K.: Lossless Compression Handbook, Elsevier, 2003, ISBN: 978-0-12-620861-0
[4] Kahrs, M., Brandenburg, K.: Applications of Digital Signal Processing to Audio and Acoustics. Kluwer Academic Publishers, 1998, ISBN: 978-0792381303
- Note:
- Time-table for winter semester 2023/2024:
- Time-table is not available yet
- Time-table for summer semester 2023/2024:
-
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri - The course is a part of the following study plans:
-
- Medical electronics and bioinformatics (compulsory elective course)
- Electronics and Communications - Audiovisual Technology and Signal Processing (compulsory course in the program)
- Electronics and Communications - Photonics (compulsory elective course)
- Electronics and Communications - Communication Networks and Internet (compulsory elective course)
- Electronics and Communications (compulsory elective course)
In order to register for the course B2M37KASA, the student must have registered for the required number of courses in the group BEZBM no later than in the same semester.