TTT4135 - Multimedia Signal Processing


Examination arrangement

Examination arrangement: Written examination
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
Written examination 100/100 4 hours D

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.

- 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.

- 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, mandatory exercises, computer exercises and semester paper.

Compulsory assignments

  • Exercises
  • Computer Excersize 1
  • Computer Excesize 2
  • Semester paper

Further on evaluation

Postponed/repeated exams may be oral.

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Course materials

Provided at course start.

Credit reductions

Course code Reduction From To
SIE2070 7.5
More on the course

Version: 1
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  SPRING 2021

No.of lecture hours: 3
Lab hours: 2
No.of specialization hours: 7

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Applied Information and Communication Technology
  • Signal Processing
  • Communication and Information Science
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Electronic Systems



Examination arrangement: Written examination

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Spring ORD Written examination 100/100 D INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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