Data Compression and Decompression Algorithms

Table of Contents Introduction.. . 2 1. info condensation.. 2 1. 1Classification of Compression 2 1. 2 Data Compression regularitys.. 3 2. lossless Compression Algorithm.. . 4 2. 1 Run-Length Encoding.. . 4 2. 1. 1 Algorithm.. . 5 2. 1. 2Complexity .. .. . 5 2. 1. 3 Advantages and disadvantage.. . 6 3.Huffmann coding.. . 6 3. 1 Huffmann encoding.. .. 6 3. 2 Algorithm.. . 7 4. Lempel-Ziv algorithm.. 7 4. 1 Lempel-Ziv78.. . 8 4. 2Encoding Algorithm.. 8 4. 3 Decoding Algorithm.. 12 5. Lempel-Ziv Welch. 14 5. 1 Encoding Algorithm.. 14 5. 2 Decoding Algorithm.. 6 References. 17 INTRODUCTION Data compression is a common requirement for most of the computerized applications. There are number of info compression algorithms, which are dedicated to compress different selective information formats. Even for a single data type there are number of different compression algorithms, which use different approaches. This paper examines lossless data compression algorithms. 1. DATA COMPRESSION In computer sciencedata compressioninvolvesencodinginformationusing fewerbitsthan the original representation.Compression is useful because it helps tighten up the consumption of resources such as data space or transmissioncapacity. Because compressed data must be decompressed to be utilize, this extra processing imposes computational or other costs through decompression. 1. 1 Classification of Compression a) Static/non-adaptive compression. b) Dynamic/adaptive compressioin. a) Static/Non-adaptive Compression Astaticmethod is one in which the mapping from the fit out of messages to the set of codewords is fixed before transmission begins, so that a given message is represented by the uniform codeword every time it appears in the message ensemble.The classic static defined-word scheme is Huffman coding. b) Dynamic/adaptive compression A code isdynamicif the mapping from the set of messages to the set of codewords changes over time. 2. 2 Data Compression Methods 1) Losseless Compres sion Lossless compression reduces bits by identifying and eliminatingstatistical redundancy. No information is lost in Lossless compression is possible because most real-world data has statistical redundancy. For example, an image may have areas of colour that do not change over several pixels kind of of coding red pixel, red pixel, the data may be encoded as 279 red pixels. Lossless compression is used in cases where it is important that the original and the decompressed data be identical, or where deviations from the original data could be deleterious. Typical examples are executable programs, text documents, and source code. Some image register formats, dealPNGorGIF, use only lossless compression 2) Loosy Compression In information technology, lossy compression is a data encoding method that compresses data by discarding (losing) some of it. The procedure aims to inimize the amount of data that needs to be held, handled, and/or transmitted by a computer. Lossy compression is most commonly used to compress multimedia data (audio, video, and still images), especially in applications such as streaming media and internet telephony. If we take a photo of a old over the sea, for example there are going to be groups of pixels with the same colour value, which can be reduced. Lossy algorithms tend to be more complex, as a result they achieve better results for bitmaps and can accommodate for the lose of data. The compressed file is an estimation of the original data.One of the disadvantages of lossy compression is that if the compressed file keeps being compressed, then the quality will degraded drastically. 2. Lossless Compression Algorithms 2. 1 Run-Length Encoding(RLE) RLE stands for Run Length Encoding. It is a lossless algorithm that only offers fair compression ratios in specific types of data. How RLE works RLE is probably the easiest compression algorithm. It replaces sequences of the same data values within a file by a wager number and a single valu e. Suppose the following string of data (17 bytes) has to be compressed ABBBBBBBBBCDEEEEFUsing RLE compression, the compressed file takes up 10 bytes and could look like this A 8B C D 4E F 2. 1. 1 Algorithm for (i=0i