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.
- describe various types of multimedia information
- define and describe basic concepts of digital signal processing
- list examples of digital signal processing applications
- apply knowledge for solution of simple signal processing problems
- define and describe basic concepts of image and video processing and analysis theory
- list examples of digital image and video processing applications
- apply knowledge for solution of simple image processing and analysis problems
Forms of Teaching
12 lectures and 1 problem solving sessionExams
The midterm exam and the final exam.Laboratory Work
|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
- Introduction. Types of multimedia information (audio signals, images and video signals).
- Signal and system representation.
- System realizations. Transfer functions.
- Signal spectrum. Digital filter banks.
- System design. Examples and problems.
- Real spectra. Signal interpolation. Non-linear filters.
- Problem solving sessions.
- Midterm exam.
- Introduction to image and video processing.
- Two dimensional signals and systems. Sampling and quantisation.
- Image transforms.
- Image enhancement.
- Image restoration.
- Image feature extraction. Image segmentation. Problem solving sessions.
- Final exam.