31-10-2012, 01:45 PM
A Review of Data Compression Techniques
Data Compression.ppt (Size: 245 KB / Downloads: 37)
Introduction
Data compression is the process of encoding data so that it takes less storage space or less transmission time than it would if it were not compressed.
Compression is possible because most real-world data is very redundant
Different Compression Techniques
Mainly two types of data Compression techniques are there.
Loss less Compression.
Useful in spreadsheets, text, executable program Compression.
Lossy less Compression.
Compression of images, movies and sounds.
Types of Loss less data Compression
Dictionary coders.
Zip (file format).
Lempel Ziv.
Entropy encoding.
Huffman coding (simple entropy coding).
Run-length encoding.
Dictionary-Based Compression
Dictionary-based algorithms do not encode single symbols as variable-length bit strings; they encode variable-length strings of symbols as single tokens.
The tokens form an index into a phrase dictionary.
If the tokens are smaller than the phrases they replace, compression occurs.
Advantages
As LZW is adaptive dictionary coding no need to transfer the dictionary explicitly.
It will be created at the decoder side.
LZW can be made really fast, it grabs a fixed number of bits from input, so bit parsing is very easy, and table look up is automatic.
Problems with the encoder
What if we run out of space?
Keep track of unused entries and use LRU (Last Recently Used).
Monitor compression performance and flush dictionary when performance is poor.
Conclusion
LZW has given new dimensions for the development of new compression techniques.
It has been implemented in well known compression format like Acrobat PDF and many other types of compression packages.
In combination with other compression techniques many other different compression techniques are developed like LZMS.