Title :
A universal data compression system
fDate :
9/1/1983 12:00:00 AM
Abstract :
A universal data compression algorithm is described which is capable of compressing long strings generated by a "finitely generated" source, with a near optimum per symbol length without prior knowledge of the source. This class of sources may be viewed as a generalization of Markov sources to random fields. Moreover, the algorithm does not require a working storage much larger than that needed to describe the source generating parameters.
Keywords :
Source coding; Context modeling; Costs; Data compression; Encoding; Helium; Image coding; Image segmentation; Partitioning algorithms; Power generation; Statistics;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1983.1056741