[The University of Leicester]

Department of Mathematics & Computer Science



Next: CO3097 Programming Secure and Distributed Systems Up: Level 3 Previous: CO3095 Software Measurement and Quality Assurance

CO3096 Compression Methods for Multimedia

CO3096 Compression Methods for Multimedia

Credits: 20 Convenor: Prof. R. Raman Semester: 2
Prerequisites: essential: CO1011, CO1016, CO1017 desirable:
Assessment: Coursework: 30% Three hour exam in January: 70%
Lectures: 36 Problem Classes: 6
Tutorials: none Private Study: 96
Labs: none Seminars: none
Project: none Other: none
Surgeries: 12 Total: 150

Explanation of Pre-requisites

There are two main prerequisites. Firstly, students should have some knowledge of how data of various kinds (numbers, characters, images and sound) are represented digitally in uncompressed format. This will be reviewed rapidly at the start of the course. Some elementary mathematics is also required. In particular, trigonometry: basic functions--$\cos$,$\sin$ and measuring angles in radians; probability: basic definitions and expected values; matrices: transposition and multiplication and recurrence relations: basic familiarity. Basic familiarity with the elements of computer systems and networks is also desirable.

Course Description

Data compression is about finding novel ways of representing data so that it takes very little storage, with the proviso that it should be possible to reconstruct the original data from the compressed version. Compression is essential when storage space is at a premium or when data needs to be transmitted and bandwidth is at a premium (which is almost always). The first thing that one learns about compression is that it is not ``one size fits all'' approach: the essence of compression is to determine characteristics of the data that one is trying to compress (typically one is looking for patterns that one can exploit to get a compact representation). This gives rise to a variety of data modelling and representation techniques, which is at the heart of compression. The convergence of the communications, computing and entertainment industries has made data compression a part of everyday life (e.g. MP3, DVD and Digital TV) and has thrown up a number of exciting new opportunities for new applications of compression technologies.

Aims

To study methods for compression of symbolic data as well as audio, image and video data. To gain an appreciation of the ubiquity and importance of compression technologies.

Objectives

Transferable Skills

The ability to combine factual knowledge with problem solving skills will pervade the course, and will benefit students within academia and in real life computing situations.

Syllabus

Introduction: Raw multimedia data representation, Transmission medium characteristics, Data compression, Adaptive and non-adaptive methods, Lossy and lossless compression, Introduction to information theory and Theoretical limits of compressibility. Compressing symbolic data: Run-length coding, Entropy coders: Huffman coding, arithmetic coding, Dictionary coders: LZ77, LZW, Other text compression methods: Block-sorting. Standard text compression utilities: compress, zip. Image compression: Monochrome, facsimile and grayscale compression, GIF compression, JPEG compression, Video compression: Frame-by-frame compression: M-JPEG. Inter-frame compression: MPEG. Audio compression: Speech coding: ADPCM; CD-quality audio: MPEG layer 3. Compression applications: Computer system applications, Communication network applications, Broadcast media applications, Consumer electronics applications, Publishing applications, Entertainment applications, Healthcare applications. Managing compressed data: Self-identifying compressed data, Error-proofing compression algorithms, Interaction between compression and other functions, Interaction between compression algorithms, Operating on compressed data, Archiving compressed data.

Reading list

Roy Hoffman, Data compression in digital systems., Chapman and Hall Digital Multimedia Standards Series, 1997.

Recommended:

Khalid Sayood, Introduction to Data Compression, 2nd ed., Morgan Kaufmann Publishers, 2000.

Background:

Andrew S. Tanenbaum, Structured Computer Organization, 4th Edition, Prentice Hall, 1999..

, The comp.compression FAQ., www.faqs.org/faqs/compression-faq/.


Next: CO3097 Programming Secure and Distributed Systems Up: Level 3 Previous: CO3095 Software Measurement and Quality Assurance

[University Home] [MCS Home] [University Index A-Z] [University Search] [University Help]

Author: S. J. Ambler, tel: +44 (0)116 252 3884
Last updated: 2002-07-11
MCS Web Maintainer
This document has been approved by the Head of Department.
© University of Leicester.