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Lossless Data Compression Techniques and Comparison between the Algorithms

Author(s):

K. Pavan Kumar Reddy , VIT Vellore; Vikranth Kanumuru, VIT Vellore; Abhishek C, VIT Vellore; Shashank Asulkar, VIT Vellore; Dr.K.Manikandan, VIT Vellore

Keywords:

Data Compression, Data Compression Techniques, Shannon-Fano Coding, Huffman Coding, Run Length Encoding

Abstract

Data Compression is a typical requirement for the greater amount of the computerized applications reacted Information. There are number of data compression technologies are available and each technology have their own advantages and disadvantages. According to the size of the data we have to choose right technology for data compression. We can also compare the different data compression technology according to different examples. Data compression is a typical necessity for the majority of the electronic applications. In this manner, the primary point of data compression is to evacuate information excess from the store or transmitting information. Data compression additionally an imperative application in field of document capacity and distributed framework as in data are to send and get from the entire framework. So Speed and execution effectiveness are likewise main consideration as far as data compression is to be utilized. In the data compression technologies we have to consider many factors like running time and space complexity of the algorithm, dataset size and cots. Above all factor are used to choose the best algorithm for data compression. The Different data compression techniques are used different data format like structured data and unstructured data. The structured data may be word document, pdf and all in textual or tabular format of all data. The best examples of unstructured data are audio, video, Image files and Body of Email messages. Mainly there are two forms of data compression: - Lossy and Lossless. But in the lossless data compression, the integrity of data is to be preserved.

Other Details

Paper ID: IJSRDV5I120459
Published in: Volume : 5, Issue : 12
Publication Date: 01/03/2018
Page(s): 1060-1062

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