Information Processing

Course Description

Types of multimedia information (audio signals, images and video signals). Formats and standards. Digital signal processing. Signal representation. Linear transforms. FIR and IIR filters. 1-D filtering. Image and video processing. Image filtering. Enhancement and reconstruction of images and video. Analysis of 1-D signals, images and video signals. Image segmentation. Information visualization. Compression basics. Protection of the information integrity and authenticity. Software tools for information processing and analysis. Applications.

General Competencies

Fundamental knowledge in digital signal processing, image and video processing in the multimedia systems. Student understands concepts of signal and image representation and decomposition in spectral domain. Student gains knowledge about FIR and IIR filters, basic methods of FIR filter design, and fundamentals of filter banks and their application to signal compression. Student understands methods for image enhancement, image restoration, image feature extraction, and image segmentation.

Learning Outcomes

  1. describe various types of multimedia information
  2. define and describe basic concepts of digital signal processing
  3. list examples of digital signal processing applications
  4. apply knowledge for solution of simple signal processing problems
  5. define and describe basic concepts of image and video processing and analysis theory
  6. list examples of digital image and video processing applications
  7. apply knowledge for solution of simple image processing and analysis problems

Forms of Teaching


12 lectures and 1 problem solving session


The midterm exam and the final exam.

Laboratory Work



After lectures

Grading Method

By decision of the Faculty Council, in the academic year 2019/2020. the midterm exams are cancelled and the points assigned to that component are transferred to the final exam, unless the teachers have reassigned the points and the grading components differently. See the news for each course for information on knowledge rating.
Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 50 % 25 % 50 % 0 %
Homeworks 50 % 10 % 0 % 0 %
Mid Term Exam: Written 50 % 30 % 0 %
Final Exam: Written 50 % 35 %
Exam: Written 50 % 50 %
Exam: Oral 50 %

Week by Week Schedule

  1. Introduction. Types of multimedia information (audio signals, images and video signals).
  2. Signal and system representation.
  3. System realizations. Transfer functions.
  4. Signal spectrum. Digital filter banks.
  5. System design. Examples and problems.
  6. Real spectra. Signal interpolation. Non-linear filters.
  7. Problem solving sessions.
  8. Midterm exam.
  9. Introduction to image and video processing.
  10. Two dimensional signals and systems. Sampling and quantisation.
  11. Image transforms.
  12. Image enhancement.
  13. Image restoration.
  14. Image feature extraction. Image segmentation. Problem solving sessions.
  15. Final exam.

Study Programmes

University undergraduate
Electronic and Computer Engineering (module)
Elective Courses (6. semester)
Information Processing (module)
(6. semester)



J. H. McClellan, R. W. Schafer, M. A. Yoder (1999.), DSP First: A Multimedia Approach, Prentice Hall
R. C. Gonzalez, R. E. Woods (2007.), Digital Image Processing, Prentice Hall
Z.-N. Li, M. S. Drew (2003.), Fundamentals of Multimedia, Prentice Hall

Laboratory exercises