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The Computer Journal 1987 30(2):149-156; doi:10.1093/comjnl/30.2.149
© 1987 by British Computer Society
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Data Compression for a Source with Markov Characteristics

J. A. Llewellyn *

Department of Computing, Engineering Building, University of Lancaster, Bailrigg, Lancaster LA1 4YR, UK

The entropy of an information source gives a lower limit to the data compression, measured as the average code/source ratio, which can be achieved without loss of information when transmitting or storing data from that source. The Huffman method for the design of a coding transformation guarantees optimum compression for a finite approximation to the source, i.e. a fixed number of source symbols (or symbol groups) and their respective probabilities. By taking sufficiently large groups, the code/source ratio can de decreased arbitrarily near to the limiting entropy.

The method to be presented in this paper takes a contrary approach and guarantees optimum compression for a preselected number of available code symbols (or symbol groups) and takes into account the statistical structure of the source in an optimum way. The use of finite state models provides a formal representation of the resulting encoding transformation, from which encoders and decoders can be designed.

The method is further extended to allow for exclusion of source strings with zero probability, but loses the absolute guarantee of optimum data compression for the given number of available code symbols.

Received May 1985.

* Department of Computing, Engineering Building, University of Lancaster, Bailrigg, Lancaster LA1 4 YR


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