Context-Based Compression
Abstract
In this chapter, we present a number of techniques that use minimal prior assumptions about the statistics of the data. Instead they use the context of the data being encoded and the past history of the data to provide more efficient compression. We will look at a number of schemes that are principally used for the compression of text. These schemes use the context in which the data occurs in different ways.
Keywords
Prediction with partial match (ppm); Burrows–Wheeler transform (BWT); Move-to-front (MTF); ACB; Dynamic Markov compression (DMC)
6.1 Overview
In previous chapters we have seen a number of techniques which use a probability model of the source to generate efficient codes. If ...
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