Improving Parse Trees for Efficient Variable-to-Fixed Length Codes

Abstract

We address the problem of improving variable-length-to-fixed-length codes (VF codes). A VF code that we deal here with is an encoding scheme that parses an input text into variable length substrings and then assigns a fixed length codeword to each parsed substring. VF codes have favourable properties for fast decoding and fast compressed pattern matching, but they are worse in compression ratio than the latest compression methods. The compression ratio of a VF code depends on the parse tree used as a dictionary. To gain a better compression ratio we present several improvement methods for constructing parse trees. All of them are heuristical solutions since it is intractable to construct the optimal parse tree. We compared our methods with the previous VF codes, and showed experimentally that their compression ratios reach to the level of state-of-the-art compression methods.