Subject description - B2M37KASA

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B2M37KASA Compression of images and signals
Roles:PV, P Extent of teaching:2P+2C
Department:13137 Language of teaching:CS
Guarantors:Vítek S. Completion:Z,ZK
Lecturers:Fliegel K., Rund F., Vencovský V., Vítek S. Credits:6
Tutors:Fliegel K., Rund F., Vencovský V., Vítek S. Semester:L


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.

Study targets:

Main goal is to introduce basic concepts of lossless and lossy compresion of audiovisual information (entropy, redundancy and irrelevancy).

Course outlines:

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.

Exercises outline:

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.


[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


Basic methods and techniques of acquiring, transmission, processing and reproduction of audiovisual signals.



Subject is included into these academic programs:

Program Branch Role Recommended semester
MPBIO1_2018 Bioinformatics PV
MPEK8_2021 Communication and information processing PV 2
MPEK5_2018 Communications Networks and Internet PV 2
MPEK2_2018 Audiovisual and Signal Processing P 2
MPEK3_2018 Photonics PV 2

Page updated 16.7.2024 17:51:31, semester: Z,L/2023-4, Z/2024-5, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)