Data compression question bank

It is difficult to measure the performance of a compression algorithm in general because its compression behaviour depends much on whether the data contains the right patterns that the algorithm looks for.
The easiest way to measure the effect of a compression is to use the compression ratio.

An additional list of the books recommended for support and for historical background reading is attached in the reading list (Appendix E).
Salomon, David A Guide to Data Compression Methods.
Springer, 2001) [ISBN 0-387-95260-8].
Wayner, Peter Compression Algorithms for Real Programmers. (London:

1. Morgan Kaufmann
2. 2000) [ISBN 0-12-788774-1]

By ‘compressing data’, we actually mean deriving techniques or, more specifically, designing efficient algorithms to:

1. 2 represent data in a less redundant fashion 2 remove the redundancy in data 2 implement coding
2. including :
3. both encoding and decoding

For example, some files are already compressed, so compressing them would not have a substantial impact

There are two kinds of compression: Lossless and Lossy

Lossy compression loses data, while lossless compression keeps all the data

With lossless compression, we don’t get rid of any data

The key approaches of data compression can be summarised as modelling + coding

Modelling is a process of constructing a knowledge system for performing compression

Coding includes the design of the code and product of the compact data form

An additional list of the books recommended for support and for historical background reading is attached in the reading list (Appendix E)

Salomon, David A Guide to Data Compression Methods

Wayner, Peter Compression Algorithms for Real Programmers

(London: Morgan Kaufmann, 2000) [ISBN 0-12-788774-1]