Multimedia Systems

  • Class 45
  • Practice 15
  • Independent work 90
Total 150

Course title

Multimedia Systems

Lecture type


Course code






Lecturers and associates

Course objectives

Audio signal in time and frequency domain; Probability density function; Frequency spectra; Rate of change; Audio signal sampling theorem; Sampling and quantization errors.
Redundancy and irrelevancy of audio signals; Acoustical characteristics of voice signal; Voice generation.
Psychoacoustic models; Formats of compressed signals; Linear prediction of coefficients (LPC).
Quantization effects; General concepts of bit-rate reduction, signal redundancy and entropy; Discrete cosine transform.
Sampling rates for video and analog-to-digital conversion; Sampling structure; Chroma subsampling; Basic DCT coder and decoder (quantization process, zigzag scanning, RLC and VLC).
Standards (e.g., audio, graphics, video); Interframe prediction; Motion compensation; Motion vectors.
Multimedia support; Standards (e.g., audio, graphics, video).
Midterm exam.
Multimedia support; Standards (e.g., audio, graphics, video).
Multimedia support; Standards (e.g., audio, graphics, video).
Streams/structures, capture/represent/transform, spaces/domains, compression/coding.
Streams/structures, capture/represent/transform, spaces/domains, compression/coding.
Real-time delivery; Quality of service (including performance); Capacity planning; Audio/video, conferencing, video-on-demand.
Final exam.

Required reading

(.), Li, Ze-Nian; Drew, Mark S.; Liu, Jiangchuan: Fundamentals of Multimedia, Second Edition, Springer, 2014.,(.), Steinmetz, Ralf; Nahrstedt, Klara: Multimedia Systems, Springer, 2004.,
(.), Shi, Yun Q; Sun, Huifang: Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards, CRC Press, 2008.,
(.), Khalid Sayood, Introduction to Data Compression, Fourth Edition, Morgan Kaufmann, 2012

Minimal learning outcomes

  • Define media signals, their representation, processing and applications
  • Distinguish source coding and entropy coding and various algorithms for media compression
  • Apply and analyze methods for predictive and transform coding of media signals
  • Describe human auditory and visual perception model and explain properties of audio and video signal
  • Explain differences between analog and digital video signal representation
  • Employ methods for image and video signal compression
  • Implement methods for multimedia compression
  • Evaluate and modify the performance of multimedia algorithms
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