October 2017
Intermediate to advanced
790 pages
46h 35m
English
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.
Prediction with partial match (ppm); Burrows–Wheeler transform (BWT); Move-to-front (MTF); ACB; Dynamic Markov compression (DMC)
In previous chapters we have seen a number of techniques which use a probability model of the source to generate efficient codes. If ...
Read now
Unlock full access