Multimedia Systems

Course Description

Multimedia technologies and systems; architecture and applications. Multimedia signal sources. Fundamentals of compression and coding. Speech signal, modeling and analysis. Parametric models; speech coding standards. Speech synthesis and recognition. Audio signal. Psychoacoustic model, audio coding principles and standards. Human visual perception model. Image formats, coding, and standards. Video signal and its properties. Spatial, time and subjective redundancy. Video compression standards. Storage, processing and transmission of multimedia content. Hardware and software implementations. Integration of multimedia content, synchronization. Integration and evaluation of multimedia algorithms. Multimedia systems and tools for design, assessment and performance optimization.

Learning Outcomes

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

Forms of Teaching








Internship visits

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 0 % 15 % 0 % 15 %
Homeworks 0 % 15 % 0 % 15 %
Attendance 0 % 5 % 0 % 5 %
Mid Term Exam: Written 0 % 30 % 0 %
Final Exam: Written 0 % 25 %
Final Exam: Oral 10 %
Exam: Written 50 % 55 %
Exam: Oral 10 %

To pass the course you need to score at least 50 points, of which: minimum 18 points on homework, laboratory exercises and attendance, a minimum of 28 points on the midterm exam and the written part of the final exam.

Week by Week Schedule

  1. Audio signal in time and frequency domain, Probability density function; Frequency spectra; Rate of change, Audio signal sampling theorem, Sampling and quantization errors
  2. Redundancy and irrelevancy of audio signals, Acoustical characteristics of voice signal, Voice generation
  3. Psychoacoustic models, Formats of compressed signals, Linear prediction of coefficients (LPC)
  4. Quantization effects, General concepts of bit-rate reduction, signal redundancy and entropy, Discrete cosine transform
  5. 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)
  6. Standards (e.g., audio, graphics, video), Interframe prediction; Motion compensation; Motion vectors
  7. Multimedia support, Standards (e.g., audio, graphics, video)
  8. Midterm exam
  9. Multimedia support, Standards (e.g., audio, graphics, video)
  10. Multimedia support, Standards (e.g., audio, graphics, video)
  11. Streams/structures, capture/represent/transform, spaces/domains, compression/coding
  12. Streams/structures, capture/represent/transform, spaces/domains, compression/coding
  13. Real-time delivery; Quality of service (including performance); Capacity planning; Audio/video, conferencing, video-on-demand
  14. Visit
  15. Final exam

Study Programmes

University undergraduate
Elective Courses (6. semester)
Elective Courses (6. semester)
[FER2-HR] Computer Engineering - module
Elective Courses (6. semester)
[FER2-HR] Electronic and Computer Engineering - module
Elective Courses (6. semester)
[FER2-HR] Information Processing - module
(6. semester)
[FER2-HR] Wireless Technologies - module
Elective Courses (6. semester)


Ze-Nian Li, Mark S. Drew, Jiangchuan Liu (2021.), Fundamentals of Multimedia, Springer Nature
Ralf Steinmetz, Klara Nahrstedt (2013.), Multimedia Systems, Springer Science & Business Media
Yun Q. Shi, Huifang Sun (2017.), Image and Video Compression for Multimedia Engineering, CRC Press
Khalid Sayood (2012.), Introduction to Data Compression, Newnes


Laboratory exercises

For students


ID 183397
  Summer semester
L2 English Level
L1 e-Learning
45 Lectures
0 Seminar
6 Exercises
15 Laboratory exercises
0 Project laboratory

Grading System

90 Excellent
78 Very Good
62 Good
50 Acceptable