Audio and Image Compression, 6 credits (TSBK35)

Main field of study

Computer Science and Engineering, Electrical Engineering, Media Technology and Engineering

Course level

Second cycle

Advancement level

A1X

Course offered for

• Media Technology and Engineering, M Sc in Engineering
• Communication and Transportation Engineering, M Sc in Engineering
• Computer Science, Master's programme

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

Probability theory and basic signal processing.

Intended learning outcomes

The course should give knowledge about methods used for data compression and how these methods are applied to audio and image signals. After taking the course, the student is expected to be able to

• Make random models for sources
• Analyze random source models
• Understand source coding methods such as huffman coding and arithmetic coding.
• Understand quantization
• Understand linear predictive coding
• Understand transform coding.
• Understand subband coding.
• Calculate coding performance for different coding methods, given random models for the sources
• Know how different coding methods are used for compression of still images, video and audio data.
• Know what methods are used in different compression standards (GIF, PNG, JPEG, MPEG, mp3, AAC, speech kodning).

Course content

Theory:

• Random signal models
• Lossless coding
• Entropy
• Huffman coding
• Arithmetic coding
• Lempel-Ziv coding
• Scalar quantization
• Vector quantization
• Linear predictive coding
• Transform coding
• Subband coding.
• Motion estimation and motion compensation.

Practical methods

• Still image coding: GIF, PNG, JPEG, JPEG-2000
• Video coding: MPEG-1/2/4
• Speech coding: CELP, GSM
• Audio coding: MPEG-1 audio layer I/II/III, Dolby Digital, AAC, Ogg Vorbis

Teaching and working methods

The course consists of lectures, lessons and computer lab work.

Examination

LAB1	Laboratory Work	U, G	1.5 credits
TEN1	Written examination	U, 3, 4, 5	4.5 credits

Grades

Four-grade scale, LiU, U, 3, 4, 5

Department

Institutionen för systemteknik

Director of Studies or equivalent

Klas Nordberg

Examiner

Harald Nautsch

Course website and other links

http://www.icg.isy.liu.se/courses/tsbk35/

Education components

Preliminär schemalagd tid: 46 h
Rekommenderad självstudietid: 114 h

Course literature

Kompletterande litteratur

Böcker

Khalid Sayood, Introduction to Data Compression
ISBN: ISBN 978-0-12-415796-5