A dictionary-based text compression technique using quaternary code

Abstract

Improving encoding and decoding time in compression technique is a great demand to modern users. In bit level compression technique, it requires more time to encode or decode every single bit when a binary code is used. In this research, we develop a dictionary-based compression technique where we use a quaternary tree instead of a binary tree for construction of Huffman codes. Firstly, we explore the properties of quaternary tree structure mathematically for construction of Huffman codes. We study the terminology of new tree structure thoroughly and prove the results. Secondly, after a statistical analysis of English language, we design a variable length dictionary based on quaternary codes. Thirdly, we develop the encoding and decoding algorithms for the proposed technique. We compare the performance of the proposed technique with the existing popular techniques. The proposed technique performs better than the existing techniques with respect to decompression speed while the space requirement increases insignificantly.