Open Access Open Access  Restricted Access Subscription Access

A Review on Various Lossless Text Data Compression Techniques


 

Compression algorithms reduce the redundancy in data representation thus increasing effective data density. Data compression is a very useful technique that helps in reducing the size of text data and storing the same amount of data in relatively fewer bits resulting in reducing the data storage space, resource usage or transmission capacity. There are a number of techniques that have been used for text data compression which can be categorized as Lossy and Lossless data compression techniques. In this paper, various lossless data compression techniques have been reviewed that are in use such as Run Length Encoding, Burrows- wheeler transform, Shannon-Fano coding, Huffman coding, Arithmetic coding, Lempel-Ziv Welch and Bit-Reduction algorithm.

Keywords

Text Data Compression, Lossless Compression, Huffman Coding, Arithmetic Coding, Bit Reduction.
User
Notifications
Font Size

Abstract Views: 246

PDF Views: 4




  • A Review on Various Lossless Text Data Compression Techniques

Abstract Views: 246  |  PDF Views: 4

Authors

Abstract


Compression algorithms reduce the redundancy in data representation thus increasing effective data density. Data compression is a very useful technique that helps in reducing the size of text data and storing the same amount of data in relatively fewer bits resulting in reducing the data storage space, resource usage or transmission capacity. There are a number of techniques that have been used for text data compression which can be categorized as Lossy and Lossless data compression techniques. In this paper, various lossless data compression techniques have been reviewed that are in use such as Run Length Encoding, Burrows- wheeler transform, Shannon-Fano coding, Huffman coding, Arithmetic coding, Lempel-Ziv Welch and Bit-Reduction algorithm.

Keywords


Text Data Compression, Lossless Compression, Huffman Coding, Arithmetic Coding, Bit Reduction.