Fundamental data compression
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 an...
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| Format: | eBook |
| Language: | Inglés |
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Oxford ; Burlington, MA :
Butterworth-Heinemann
2006.
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| Edition: | 1st edition |
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| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627425506719 |
Table of Contents:
- Front Cover; Fundamental Data Compression; Copyright Page; Contents; Preface; Chapter 1. Introduction; 1.1 Data compression problems; 1.2 Lossless and lossy compression; 1.3 Deriving algorithmic solutions; 1.4 Measure of compression quality; 1.5 Limits on lossless compression; Summary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 2. Coding symbolic data; 2.1 Information, data and codes; 2.2 Symbolic data; 2.3 Variable length codes; 2.4 Elementary information theory; 2.5 Data compression in telecommunication; 2.6 Redundancy; 2.7 Compression algorithms; Summary
- Learning outcomesExercises; Laboratory; Assessment; Bibliography; Chapter 3. Run-length algorithms; 3.1 Run-length; 3.2 Hardware data compression (HDC); 3.3 Algorithm Design; Summary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 4. Huffman coding; 4.1 Static Huffman coding; 4.2 Shannon-Fano approach; 4.3 Optimal Huffman codes; 4.4 Implementation efficiency; 4.5 Extended Huffman coding; Summary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 5. Adaptive Huffman coding; 5.1 Adaptive approach; 5.2 Compressor; 5.3 Decompressor
- 5.4 Disadvantages of Huffman algorithmsSummary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 6. Arithmetic coding; 6.1 Probabilities and subintervals; 6.2 Model and coders; 6.3 Simple case; 6.4 General case; Summary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 7. Dictionary - based compression; 7.1 Patterns in a string; 7.2 LZW coding; 7.3 LZ77 family; 7.4 LZ78 family; 7.5 Applications; 7.6 Comparison; Summary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 8. Prediction and transforms
- 8.1 Predictive approach8.2 Move to Front coding; 8.3 Burrows-Wheeler Transform (BWT); 8.4 Transform approach; 8.5 Discrete Cosine Transform (DCT); 8.6 Subband coding; 8.7 Wavelet transforms; Summary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 9. Audio compression; 9.1 Modelling sound; 9.2 Sampling; 9.3 Quantisation; 9.4 Compression performance; 9.5 Speech compression; 9.6 Music compression; Summary; Learning outcomes; Exercises; Assessment; Bibliography; Chapter 10. Image compression; 10.1 Image data; 10.2 Bitmap images; 10.3 Vector graphics
- 10.4 Bitmap and vector graphics10.5 Colour; 10.6 Classifying images by colour; 10.7 Classifying images by appearance; 10.8 Image compression; Summary; Learning outcomes; Exercises; Laboratory; Assessment; Bibliography; Chapter 11. Video compression; 11.1 Analogue video; 11.2 Digital video; 11.3 Moving pictures; 11.4 MPEG; 11.5 Basic principles; 11.6 Temporal compression algorithms; 11.7 Group of pictures; 11.8 Motion estimation; 11.9 Work in different video formats; Summary; Learning outcomes; Exercises; Assessment; Bibliography; Appendix A. Brief history; Appendix B. Matrices
- Appendix C. Fourier series and harmonic analysis
