Analysis of Huffman Coding and Lempel–Ziv–Welch (LZW) Coding as Data Compression Techniques

Gajendra Sharma¹

Section:Research Paper, Product Type: Journal-Paper
Vol.8 , Issue.1 , pp.37-44, Feb-2020

Online published on Feb 28, 2020

Copyright © Gajendra Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Huffman Coding is a statistical data compression providing to reduce code length that is used to represent the symbols of an alphabet. This is a standard technique for the creation of Minimum-Redundancy Codes. LZW is a dictionary based compression tool which is widely popular. This implies that instead of tabulating character counts and building trees LZW encodes data by referencing a dictionary. Compared to any adaptive and dynamic compression method, the concept is to initiate with an initial model, read data and update the framework and data encoding. In this paper, we investigated the following question: Which coding, LZW or Huffman, is more suitable compared to each other? The implemented results show that LZW requires no prior information about the input data stream, and also LZW can compress the input stream in one single pass allowing fast execution. LZW coding is more feasible when the high compression ratio and less compression-decompression time are needed.

Key-Words / Index Term :
Digital data, input symbols, compression, minimum-redundancy, LZ Wcoding, Huffman coding

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