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Difference between lossless data compression vs lossy data compression

Data compression has become popular as compression reduces size of a file which helps save space when storing and save time when transmitting it. Data compression can be applied to text, image, sound and video information. Applications of data compressions are many which include generic file compression, multimedia, communication and database maintained by Google servers. There are two main types of compressions e.g. lossless and lossy. Following is the difference between them.

Lossless Data Compression

In lossless data compression original data is exactly restored after decompression. Mainly used for text data compression and decompression. It can also be applied to image compression. The popular algorithms are the run length coding,huffman coding, adaptive huffman coding,arithmetic coding and dictionary based coding etc.

Run Length Encoding

Algorithm:
Run length encoding is simple form of data compression. Here consecutive runs of data are stored as single data value and count(indicating how many times that data is repeating) It is useful for compressing simple graphic images e.g. icons as well as line drawings.
EXAMPLE:
Input: ZZZZZZZZZZZZCZZZZZZZZZZZZCCCZZZZZZZZZZZZZZZZZZZZZZZZC
Output:
12ZC12Z3C24ZC

Huffman coding

It is one of the well known algorithm for data compression. Following is the way it works:
• It assigns bit string to each symbol.
• Higher the frequency a symbol will have,shorter the bit string it will be represented with.
• Two symbols having least frequencies will be represented by same length bit strings.
They both will have identical bit strings except the last bit in the strings.
Other technique which is the variation of Huffman coding is the Adaptive Huffman coding as described below.

Adaptive Huffman coding is adaptive coding technique based on Huffman coding. Following is the procedure used in encoder decoder of the adaptive huffman coding technique

Dictionary based coding

Techniques that are based on using a dynamic dictionary to be able to compress the data are LZ77, LZ78 and LZW. The most popular among them is LZW algorithm.

arithmetic coding

Unlike Huffman coding which assigns a bit string to each symbol,the arithmetic coding algorithm assigns a unique tag for the entire sequence. Following algorithm is implemented in arithmetic encoder.

Lossy Data Compression

In lossy data compression original data is not exactly restored after decompression and accuracy of re-construction is traded with efficiency of compression. Mainly used for image data compression and decompression. Compression ratio is high compare to lossless data compression technique. Lossy data compression algorithms are transform coding(for example, discrete cosine tranform), Karhunen-Loeve Transform (KLT) and wavelet based coding(for example, continuous wavelet transform-CWT and Discrete wavelet transform(DWT).

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