Data Compression and Decompression Algorithms

Table of Contents Introduction.. . 2 1. Data condensing.. 2 1. 1Classification of Compression 2 1. 2 Data Compression methods.. 3 2. lossless Compression algorithmic program.. . 4 2. 1 Run-Length En cryptanalytics.. . 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 foundation garment Data adjureion is a common requirement for most of the computerized applications. in that location are number of selective information crush algorithms, which are dedicated to compress variant data formats. Even for a single data pillow slip there are number of different compression algorithms, which use different approaches. This paper examines lossless data compression algor ithms. 1. DATA COMPRESSION In computer sciencedata compressioninvolvesencodinginformation apply fewerbitsthan the airplane pilot representation.Compression is useful because it helps reduce the consumption of re commencements such as data space or transmittalcapacity. Because matte data mustiness be decompressed to be use, this extra processing imposes computational or different costs through decompression. 1. 1 Classification of Compression a) Static/non-adaptive compression. b) changing/adaptive compressioin. a) Static/Non-adaptive Compression Astaticmethod is virtuoso in which the map from the set of messages to the set of codewords is fixed before transmission begins, so that a given message is represented by the akin codeword every time it appears in the message ensemble.The classic static defined-word strategy is Huffman coding. b) Dynamic/adaptive compression A code isdynamicif the mapping from the set of messages to the set of codewords deviates over time. 2. 2 Da ta Compression Methods 1) Losseless Compression Lossless compression reduces bits by identifying and eliminatingstatistical redundancy. No information is muzzy 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 instead of coding red pixel, red pixel, the data may be encoded as 279 red pixels. Lossless compression is utilise 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 file formats, likePNGorGIF, use except lossless compression 2) Loosy Compression In information technology, lossy compression is a data encoding method that compresses data by discarding (losing) almost of it. The procedure aims to inimize the amount of data that needs to be held, handled, and/or hereditary 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 sunset over the sea, for example there are going to be groups of pixels with the same colour value, which contribute 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 go forth 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 decent compression ratios in unique(predicate) types of data. How RLE works RLE is probably the easiest compression algorithm. It replaces sequences of the same data values at heart a file by a count number and a single value. 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