Comparison of Huffman algorithm and Lempel-Ziv algorithm for audio, image and text compression

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Document Type

Conference Proceeding

Source Title

8th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2015

Publication Date

1-25-2016

Abstract

In digital communications, it is necessary to compress the data for a faster and more reliable transmission. As such, the data should undergo source encoding, also known as data compression, which is the process by which data are compressed into a fewer number of bits, before transmission. Also, source encoding is essential to limit file sizes for data storage. Two of the most common and most widely used source encoding techniques are the Huffman Algorithm and Lempel-Ziv Algorithm. The main objective of this research is to identify which technique is better in text, image and audio compression applications. The files for each data type were converted into bit streams using an analog-to-digital converter and pulse code modulation. The bit streams underwent compression through both compression algorithms and the efficiency of each algorithm is quantified by measuring their compression ratio for each data type. © 2015 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2015.7393210

Disciplines

Manufacturing

Keywords

Data compression (Telecommunication); Image compression

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