![]() | Department of Mathematics & Computer Science | |||
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Credits: 20 | Convenor: Prof. R. Raman | Semester: 1 |
Prerequisites: | essential: CO1011, CO1016, CO1017 | |
Assessment: | Coursework: 30% | Three hour exam in May/June: 70% |
Lectures: | 36 | Problem Classes: | 6 |
Tutorials: | none | Private Study: | 96 |
Labs: | none | Seminars: | none |
Project: | none | Other: | none |
Surgeries: | 12 | Total: | 150 |
Subject Skills
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-,
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 modeling 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.
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
Recommended:
Roy Hoffman, Data compression in digital systems, Chapman and Hall Digital Multimedia Standards Series, 1997.
Khalid Sayood, Introduction to Data Compression, Morgan Kaufmann Publishers, 2000 (2nd edition).
Background:
Andrew S. Tanenbaum, Structured Computer Organization, Prentice Hall, 1999 (4th edition).
Jean-loup Gailly, The comp.compression FAQ, www.faqs.org/faqs/compression-faq/.
Author: N. Rahman, tel: +44 (0)116 252 3902Resources
Course notes, web page, study guide, worksheets, handouts, lecture
rooms with a computer to CFS, data projector, two OHPs, past
courseworks and examination papers.
Module Evaluation
Course questionnaires, course review.
Next: CO3097 Programming Secure and Distributed Systems
Up: Year 3
Previous: CO3095 Software Measurement and Quality Assurance
Last updated: 2003-09-23
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This document has been approved by the Head of Department.
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