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Fundamental Data Compression - Ida Mengyi Pu

Fundamental Data Compression

Paperback

Published: 11th January 2006
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Fundamental Data Compression provides all the information students need to be able to use this essential technology in their future careers. A huge, active research field, and a part of many people's everyday lives, compression technology is an essential part of today's Computer Science and Electronic Engineering courses.
With the help of this book, students can gain a thorough understanding of the underlying theory and algorithms, as well as specific techniques used in a range of scenarios, including the application of compression techniques to text, still images, video and audio. Practical exercises, projects and exam questions reinforce learning, along with suggestions for further reading.
* Dedicated data compression textbook for use on undergraduate courses
* Provides essential knowledge for today's web/multimedia applications
* Accessible, well structured text backed up by extensive exercises and sample exam questions

Prefacep. xvii
Introductionp. 1
Data compression problemsp. 3
Compressionp. 3
Decompressionp. 4
Lossless and lossy compressionp. 5
Deriving algorithmic solutionsp. 7
Measure of compression qualityp. 11
Limits on lossless compressionp. 13
Summaryp. 15
Learning outcomesp. 15
Exercisesp. 15
Laboratoryp. 16
Assessmentp. 17
Bibliographyp. 17
Coding symbolic datap. 19
Information, data and codesp. 19
Symbolic datap. 20
Variable length codesp. 23
Modellingp. 23
Unique decodabilityp. 24
Prefix codes and binary treesp. 25
Prefix codes and unique decodabilityp. 27
Kraft inequalityp. 28
Elementary information theoryp. 32
Entropyp. 34
Optimum codesp. 38
Data compression in telecommunicationp. 39
Redundancyp. 40
Compression algorithmsp. 43
Summaryp. 46
Learning outcomesp. 46
Exercisesp. 46
Laboratoryp. 47
Assessmentp. 47
Bibliographyp. 47
Run-length algorithmsp. 49
Run-lengthp. 49
Hardware data compression (HDC)p. 50
Encodingp. 51
Decodingp. 52
Algorithm Designp. 52
Summaryp. 63
Learning outcomesp. 63
Exercisesp. 64
Laboratoryp. 64
Assessmentp. 64
Bibliographyp. 65
Huffman codingp. 67
Static Huffman codingp. 67
Huffman approachp. 69
Huffman compression algorithmp. 71
Huffman decompression algorithmp. 74
Shannon-Fano approachp. 75
Shannon-Fano algorithmp. 77
Optimal Huffman codesp. 81
Implementation efficiencyp. 82
Extended Huffman codingp. 86
Summaryp. 87
Learning outcomesp. 87
Exercisesp. 88
Laboratoryp. 89
Assessmentp. 89
Bibliographyp. 90
Adaptive Huffman codingp. 91
Adaptive approachp. 91
Compressorp. 92
Encoding algorithmp. 94
Decompressorp. 95
Decoding algorithmp. 97
Disadvantages of Huffman algorithmsp. 98
Summaryp. 98
Learning outcomesp. 98
Exercisesp. 99
Laboratoryp. 99
Assessmentp. 99
Bibliographyp. 99
Arithmetic codingp. 101
Probabilities and subintervalsp. 101
Model and codersp. 103
Simple casep. 107
Encodingp. 108
Decodingp. 109
General casep. 109
Compression algorithmp. 111
Decompression algorithmp. 112
Unique decodabilityp. 112
Advantages of using fractionsp. 113
Renormalisationp. 113
Summaryp. 114
Learning outcomesp. 114
Exercisesp. 114
Laboratoryp. 115
Assessmentp. 115
Bibliographyp. 115
Dictionary-based compressionp. 117
Patterns in a stringp. 118
LZW codingp. 119
Encodingp. 119
Decodingp. 125
LZ77 familyp. 129
Prefix matchp. 129
A typical compression stepp. 130
Decompression algorithmp. 134
Implementation issuesp. 136
LZ78 familyp. 136
Encodingp. 137
Decodingp. 138
Applicationsp. 139
Comparisonp. 140
Summaryp. 140
Learning outcomesp. 141
Exercisesp. 141
Laboratoryp. 142
Assessmentp. 142
Bibliographyp. 144
Prediction and transformsp. 145
Predictive approachp. 145
Encodingp. 148
Decodingp. 149
Move to Front codingp. 149
Burrows-Wheeler Transform (BWT)p. 151
Transform approachp. 156
Orthogonal transformp. 161
Discrete Cosine Transform (DCT)p. 163
Subband codingp. 164
Wavelet transformsp. 165
Scale-varying basis functionsp. 166
Summaryp. 167
Learning outcomesp. 167
Exercisesp. 168
Laboratoryp. 169
Assessmentp. 170
Bibliographyp. 170
Audio compressionp. 171
Modelling soundp. 171
Samplingp. 173
Nyquist frequencyp. 175
Quantisationp. 176
Scalar quantisationp. 178
Uniform quantisersp. 179
Non-uniform quantisersp. 180
Compression performancep. 181
Speech compressionp. 183
Speech codersp. 183
Predictive approachesp. 184
Silence compressionp. 184
Pulse code modulation (ADPCM)p. 185
Music compressionp. 185
Streaming audiop. 185
MIDIp. 186
Summaryp. 186
Learning outcomesp. 186
Exercisesp. 187
Assessmentp. 188
Bibliographyp. 188
Image compressionp. 189
Image datap. 189
Resolutionp. 190
Bitmap imagesp. 191
Displaying bitmap imagesp. 191
Vector graphicsp. 192
Storing graphic componentsp. 192
Displaying vector graphic imagesp. 193
Bitmap and vector graphicsp. 193
Colourp. 194
RGB colour modelp. 194
RGB representation and colour depthp. 195
LC representationp. 195
Classifying images by colourp. 196
Classifying images by appearancep. 197
Image compressionp. 198
Lossless image compressionp. 199
Greyscale and colour imagesp. 201
Lossy compressionp. 204
JPEG (still) image compression standardp. 206
Image file formatsp. 206
Summaryp. 207
Learning outcomesp. 207
Exercisesp. 208
Laboratoryp. 209
Assessmentp. 210
Bibliographyp. 210
Video compressionp. 211
Analogue videop. 211
Digital videop. 212
Moving picturesp. 212
MPEGp. 213
Basic principlesp. 213
Temporal compression algorithmsp. 213
Group of picturesp. 215
Motion estimationp. 216
Work in different video formatsp. 216
Summaryp. 217
Learning outcomesp. 217
Exercisesp. 217
Assessmentp. 217
Bibliographyp. 217
Appendicesp. 219
Brief historyp. 219
Matricesp. 223
Special matricesp. 223
Matrix operationsp. 225
Determinantsp. 226
Orthogonal matrixp. 227
Inner productp. 228
Vector spacep. 229
Fourier series and harmonic analysisp. 231
Fourier seriesp. 231
Convergent seriesp. 232
Euler's identityp. 233
Pseudocode notationp. 235
Valuesp. 235
Typesp. 235
Operationsp. 235
Priorityp. 236
Data structuresp. 236
Other reserved wordsp. 236
Control keywordsp. 236
Examples of sequential structuresp. 237
Notationp. 239
Indexp. 241
Table of Contents provided by Ingram. All Rights Reserved.

ISBN: 9780750663106
ISBN-10: 0750663103
Audience: General
Format: Paperback
Language: English
Number Of Pages: 246
Published: 11th January 2006
Publisher: Elsevier Science & Technology
Country of Publication: GB
Dimensions (cm): 24.13 x 18.19  x 1.58
Weight (kg): 0.48