Understanding Compression

Name: Understanding Compression
Author: Colt McAnlis

Data Compression for Modern Developers

Specificaties

Paperback, 242 blz. | Engels

O'Reilly | 1e druk, 2016

ISBN13: 9781491961537

Rubricering

Hoofdrubriek : Computer en informatica

Juridisch :

O'Reilly 1e druk, 2016 9781491961537

Verwachte levertijd ongeveer 16 werkdagen

42,47

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Samenvatting

If you want to attract and retain users in the booming mobile services market, you need a quick-loading app that won’t churn through their data plans. The key is to compress multimedia and other data into smaller files, but finding the right method is tricky. This witty book helps you understand how data compression algorithms work—in theory and practice—so you can choose the best solution among all the available compression tools.

With tables, diagrams, games, and as little math as possible, authors Colt McAnlis and Aleks Haecky neatly explain the fundamentals. Learn how compressed files are better, cheaper, and faster to distribute and consume, and how they’ll give you a competitive edge.

-Learn why compression has become crucial as data production continues to skyrocket
-Know your data, circumstances, and algorithm options when choosing compression tools
-Explore variable-length codes, statistical compression, arithmetic numerical coding, dictionary encodings, and context modeling
-Examine tradeoffs between file size and quality when choosing image compressors
-Learn ways to compress client- and server-generated data objects
-Meet the inventors and visionaries who created data compression algorithms

Specificaties

ISBN13:9781491961537

Trefwoorden:Data Compression

Taal:Engels

Bindwijze:paperback

Aantal pagina's:242

Uitgever:O'Reilly

Druk:1

Verschijningsdatum:3-8-2016

Hoofdrubriek:Computer en informatica

Inhoudsopgave

Foreword
Preface

1. Let’s Not Be Boring
-The Five Buckets of Compression Algorithms
-Claude Shannon Is Infuriating!
-The Only Thing You Need to Know about Data Compression

2. Do Not Skip This Chapter
-Understanding Binary
-Information Theory

3. Breaking Entropy
-Understanding Entropy
-What This Entropy Stuff Is Good For
-Understanding Probability
-Breaking Entropy
-Information Theory Versus Data Compression

4. Variable-Length Codes
-Morse Code
-Probability, Entropy, and Codeword Size
-Variable-Length Codes

5. Statistical Encoding
-Statistically Compressing to Entropy
-Huffman Coding
-Arithmetic Coding
-Asymmetric Numeral Systems
-Practical Compression: Which Statistical Algorithm Do I Choose?

6. Adaptive Statistical Encoding
-Locality Matters for Entropy
-Adaptive VLC Encoding
-Adaptive Arithmetic Coding
-Adaptive Huffman Coding
-The Modern Choice

7. Dictionary Transforms
-A Basic Dictionary Transform
-The Lempel-Ziv Algorithm
-Collect Them All!

8. Contextual Data Transforms
-Run-Length Encoding
-Delta Coding
-Move-to-Front Coding
-Burrows–Wheeler Transform

9. Data Modeling
-The Chains of Markov
-Prediction by Partial Matching
-Context Mixing
-The Next Big Thing?

10. Switching Gears
-Media-Specific Compression
-General-Purpose Compression
-Compression in Practice

11. Evaluating Compression
-Compression Usage Scenarios
-Compression Need
-Compression Ratio
-Compression Performance
-Decompression Performance
-Ability to Decode-Stream
-Comparing Compressors

12. Compressing Image Data Types
-Understanding Quality Versus File Size
-Image Dimensions Are Important
-Choosing the Correct Image Format
-GPU Texture Formats
-Vector Formats
-Eyes on the Prize

13. Serialized Data
-Understanding Common Use Cases
-Issues with Serialized Formats
-Smaller Serialized Data

14. Lossy Data Compression

15. Making the World a Little Smaller
-Data Compression and You
-Data Compression and the Bottom Line
-Making Your Users’ Lives a Little More Magical and Less Expensive
-Thinking About What’s Next in Technology

Glossary of Compression Words
Index