Study On Universal Lossless Data Compression by using Context Dependence Multilevel Pattern Matching Grammar Transform

Universal lossless data compression with side information by using a conditional MPM grammar transform

A grammar transform is a transformation that converts any data sequence to be compressed into a grammar from which the original data sequence can be fully reconstructed. In a grammar-based code, a data sequence is first converted into a grammar by a grammar transform and then losslessly encoded. Among several recently proposed grammar transforms is the multilevel pattern matching (MPM) grammar ...

Efficient universal lossless data compression algorithms based on a greedy sequential grammar transform - Part one: Without context models

A grammar transform is a transformation that converts any data sequence to be compressed into a grammar from which the original data sequence can be fully reconstructed. In a grammar-based code, a data sequence is first converted into a grammar by a grammar transform and then losslessly encoded. In this paper, a greedy grammar transform is first presented; this grammar transform constructs sequ...

Universal lossless compression via multilevel pattern matching

A universal lossless data compression code called the multilevel pattern matching code (MPM code) is introduced. In processing a finite-alphabet data string of length , the MPM code operates at (log log ) levels sequentially. At each level, the MPM code detects matching patterns in the input data string (substrings of the data appearing in two or more nonoverlapping positions). The matching pat...

Efficient universal lossless data compression algorithms based on a greedy sequential grammar transform .2. With context models

Architecture for Efficient Implementation of the YK Lossless Data Compression Algorithm

The YK (Yang-Kieffer) algorithm [1,2] is a sequential lossless data compression built upon an efficient greedy grammar transform. This grammar transform constructs a sequence of irreducible context-free grammars from which the original data sequence can be recovered incrementally. The transform sequentially parses the original data into nonoverlapping variable-length phrases, and updates the gr...