Course - Multimedia Signal Processing - TTT4135
Multimedia Signal Processing
Choose study yearLessons are not given in the academic year 2024/2025
About
About the course
Course content
The course treats multimedia presentations (speech, audio, images, video and interactivity) and their characteristics, perception of audio visual information as well as principles and methods for digital processing of audio visual information for representation, presentation and analysis of the different signal types. The main focus is on digital signal compression, multimedia systems, interactivity, estimation and detection using machine learning and multimedia presentations
Learning outcome
Learning goals: The subject shall provide an introduction to our perception of speech, audio, music, image and video to be able to understand advanced techniques, algorithms and concepts for digital processing of multimedia presentations. The processing will be highlighted by applications from multimedia systems.
Knowledge:
- understand different characterisations of sound and images in the time domain as well as in the frequency domain and their interrelationships ,
- understand human perception of sound and images,
- know the principles and technologies of compression algorithm for sound and images and their application in a digital system,
- know the principles and technologies for machine learning used on multimedia signals - know the principles and technologies of several important standards and their typical application scenarios and - strengthen the candidates methodology and technical insight within multimedia systems.
Skills:
- combine previous knowledge and skills within mathematics, statistics and programming with new theory to solve practical problems within sound and image processing,
- understand block diagrams for compression schemes for sound and image systems and understand signal decomposition, quantisation and coding within these and - understand estimation and detection of multimedia signal using machine learning.
- training in active use of the topic by analysing and understanding applications of multimedia signal processing within multimedia systems in addition to challenging their critical thinking and attitudes towards today`s established knowledge within the area.
General competencies:
- quality evaluations and use of sound and images in typical applications within entertainment and - when relevant the candidate shall be able to understand the topics in a broader technical, financial and commercial context and collaborate on solving a practical project.
Learning methods and activities
Lectures, exercises and computer exercises.
Further on evaluation
The grades in the subject are based on 2 parts: a final written exam (40%) and a portfolio (60%). The final written exam is letter graded. The portfolio includes 3 computer based assignments (20% each). Each of the 3 computer assignments requires the hand in of a report answering the theoretical answers and providing the computer generated result.
There are weekly scheduled tutorial times, where the students can meet the tutor and get feedback and help on the computer assignments. No other written feedback is given during the working period. After submission a written feedback is provided to the students together with the grade for the part. The assignment and all information on the hand in, tutoring and other information about the computer assignments are provided on the courses blackboard area.
The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade.
If there is a re-sit examination in August, the examination form may be changed from written to oral. If the exam is to be repeated, the whole course needs to be taken.
Recommended previous knowledge
TTT4120 Digital Signal Processing.
Course materials
Provided at course start.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| SIE2070 | 7.5 sp |
Subject areas
- Applied Information and Communication Technology
- Signal Processing
- Communication and Information Science
- Technological subjects