Data Compression: The Complete ReferenceData compression is one of the most important techniques in computing engineering. From archiving data to CD-ROMs and from coding theory to image analysis, many facets of computing make use of data compression in one form or another. This book is intended to provide an overview of the many different types of compression: it includes a taxonomy, an analysis of the most common systems of compression, discussion of their relative benefits and disadvantages, and their most common usages. Readers are presupposed to have a basic understanding of computer science: essentially the storage of data in bytes and bits and computing terminology, but otherwise this book is self-contained. The book divides naturally into four main parts based on the main branches of data compression: run length encoding, statistical methods, dictionary-based methods, and lossy image compression (where in contrast to the other techniques, information in the data may be lossed but an acceptable standard of image quality retained). Detailed descriptions of many of the most well-known compression techniques are covered including: Zip, BinHex, Huffman coding, GIF and many others. |
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abcdmnop Alamitos algorithm alphabet arithmetic coding arithmetic encoder array ASCII ASCII codes assigned assume average binary bitmap bytes calculate character codewords coefficients color compressed stream compression method compression ratio Computer Society Press contains context counts Data Compression Data Compression Conference data unit DC coefficient decoder decompressed dictionary digits domain entry error example Exercise Figure followed frequency Golomb code Hamming distance Hilbert curve Huffman codes IEEE Computer Society image compression input stream integer iteration JBIG JPEG L-systems Laplace distribution literal log2 look-ahead buffer Lossless lossy match length matrix node nonzero original output stream parameter parity bit phrase pixels pointer polynomial prediction prefix probability quadrant quadtree quantized range result run length samples scan search buffer Section selected Shannon-Fano shows Space-Filling Curves step stored string swiss symbol token total number transformation tree unary code update variable-size codes variance word zero groups