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Abstract

Data compression is the process of converting an input data stream or the source stream or the original raw data into another data stream that has a smaller size. data compression is popular because of two reasons.

Description of Data Compression Techniques


1) People like to accumulate data and hate to throw anything away. No matter however large a storage device may be, sooner or later it is going to overflow. Data compression seems useful because it delays this inevitability

2) People hate to wait a long time for data transfer. There are many known methods of data compression. They are based on the different ideas and are suitable for different types of data.

They produce different results, but they are all based on the same basic principle that they compress data by removing the redundancy from the original data in the source file. The idea of compression by reducing redundancy suggests the general law of data compression, which is to "assign short codes to common events and long codes to rare events".

Data compression is done by changing its representation from inefficient to efficient form.The main aim of the field of data compression is of course to develop methods for better and better compression. Experience shows that fine tuning an algorithm to squeeze out the last remaining bits of redundancy from the data gives diminishing returns. Data compression has become so important that some researches have proposed the "simplicity and power theory".

Specifically it says, data compression may be interpreted as a process of removing unnecessary complexity in information and thus maximizing the simplicity while preserving as much as possible of its non redundant descriptive power.