Image and Video Compression (Sommersemester 2017)

Dozent Eckehard Steinbach, Alexandra Zayets
Hörerkreis siehe TUMonline
Vortragssprache Englisch
Umfang 4 SWS
Termine siehe TUMonline
Anmeldung siehe TUMonline


Ziel (erwartete Lernergebnisse und erworbene Kompetenzen)

At the end of the module students are able to apply selected concepts from information theory to video coding. The participants are able to derive the main fundamental bounds of both lossless and lossy compression. The students also gain a deep understanding of modern still image and video compression standards and are able to judge why particular techniques and algorithms are used in theses standards. They are able to evaluate the performace of a proposed image and video compression schemes and predict its complexity.


Theory and practice of digital still image and video compression. Detailed treatment of fundamental concepts and explanation of the relationship to specific algorithms employed in existing and emerging compression standards. Content: Motivation for image and video compression, review of important concepts from Information Theory, scalar and vector quantization, human visual perception, transform coding, resolution pyramids and subband coding, still image compression standards (JPEG, JPEG 2000), interframe coding, differential PCM, motion compensated prediction, video compression standards (H.26x, MPEG x).

Inhaltliche Voraussetzungen

Linear Algebra, Digital Signal Processing, Information Theory, Analog and Digital Video Signals

The following modules should be passed before taking the course:
- Information Theory and Source Coding

It is recommended to take the following modules additionally:
- Image and Video Compression Lab

Lehr- und Lernmethode

Lerning method:
In addition to the individual methods of the students consolidated knowledge is aspired by repeated lessons in exercises and tutorials.

Teaching method:
During the lectures students are instructed in a teacher-centered style. The exercises are held in a student-centered way.


Knowledge-based learning results are examined during a written midterm exam with 60 minutes duration and a written final exam with 90 minutes duration.

The final grade is composed of the following elements:
- 30 % midterm exam
- 70 % final exam

The midterm exam focuses on the solution of problems similar to the ones discussed in the tutorials. The final exam additionally requires the transfer of the learned methods to more complex problems.


rendered: 2017-09-21 06:59:33