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
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
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
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
Basic Types Of Data Compression
are two basic types of data compression.
1. Lossy compression
lossy compression some information is lost during the processing, where the image
data is stored into important and unimportant data. The system then discards the
It provides much higher compression rates but there will be
some loss of information compared to the original source file. The main advantage
is that the loss cannot be visible to eye or it is visually lossless. Visually
lossless compression is based on knowledge about colour images and human perception.
In this type
of compression no information is lost during the compression and the decompression
process. Here the reconstructed image is mathematically and visually identical
to the original one. It achieves only about a 2:1 compression ratio. This type
of compression technique looks for patterns in strings of bits and then expresses
them more concisely.
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