AN APPROACH TO DATA COMPRESSION TECHNIQUE

Abstract

This report surveys a variety of data compression methods. Lots of data has been already stored in the physical media. But it is not the end, it keeps increasing with time. Therefore collecting, managing and storing are very important. The aim of data compression is to reduce redundancy in stored or communicated data, thus increasing effective data density. Data compression has important application in the areas of file storage and distributed systems. Concepts from information theory, as they relate to the goals and evaluation of data compression methods, are discussed briefly. Most of the data compression algorithm developed on entropy based and dictionary based and some of the algorithms are based on the combination. In growing data environment many data compression came. Many of them work well in their field. Some of them are lossless and some are loosy. Lossy can be applied only on the image and video compression. And lossless can be used where we want our data to be fully recovered, for example text. Some of the data compression algorithm evolved over the time is run length coding, Huffman coding, Shannon-Fano coding, arithmetic coding, LZW coding. For text and video compression we have JPEG, MPEG formats that stores data in very compressible manner. But increasing data forces the researchers to improve their data compression algorithm. That makes us to motivate to design a new algorithm. This thesis presents a completely new idea and its implemented software of data compression. This data compression uses a very different representation system. Algorithm depends on converting conventional power of 2 bit representation into compressed form of power of 3, bit representation. The representation in power of 3 is another form to represent any number like power of 2 with some slight change. This algorithm is used to applying recursively on partially compressed data that makes it to give theoretically high compression ratio. By using this representation we are going to show here how the new representation will be used and how it can help in the data compression. And also we have presented an algorithm on the basis of this design. The implemented software application shows how good it is. This algorithm has the capability to give a very highly compressive data. So it has the great chance to be used in many data repository and communication system. And also this algorithm requires lots of work to be done by researchers.