Librería Portfolio

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



Chapter 1Let's Not Be Boring
The Five Buckets of Compression Algorithms
Claude Shannon Is Infuriating!
The Only Thing You Need to Know about Data Compression
Chapter 2Do Not Skip This Chapter
Understanding Binary
Information Theory
Chapter 3Breaking Entropy
Understanding Entropy
What This Entropy Stuff Is Good For
Understanding Probability
Breaking Entropy
Information Theory Versus Data Compression
Chapter 4Variable-Length Codes
Morse Code
Probability, Entropy, and Codeword Size
Variable-Length Codes
Chapter 5Statistical Encoding
Statistically Compressing to Entropy
Huffman Coding
Arithmetic Coding
Asymmetric Numeral Systems
Practical Compression: Which Statistical Algorithm Do I Choose?
Chapter 6Adaptive Statistical Encoding
Locality Matters for Entropy
Adaptive VLC Encoding
Adaptive Arithmetic Coding
Adaptive Huffman Coding
The Modern Choice
Chapter 7Dictionary Transforms
A Basic Dictionary Transform
The Lempel-Ziv Algorithm
Collect Them All!
Chapter 8Contextual Data Transforms
Run-Length Encoding
Delta Coding
Move-to-Front Coding
Burrows-Wheeler Transform
Chapter 9Data Modeling
The Chains of Markov
Prediction by Partial Matching
Context Mixing
The Next Big Thing?
Chapter 10Switching Gears
Media-Specific Compression
General-Purpose Compression
Compression in Practice
Chapter 11Evaluating Compression
Compression Usage Scenarios
Compression Need
Compression Ratio
Compression Performance
Decompression Performance
Ability to Decode-Stream
Comparing Compressors
Chapter 12Compressing 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
Chapter 13Serialized Data
Understanding Common Use Cases
Issues with Serialized Formats
Smaller Serialized Data
Chapter 14Lossy Data Compression
Chapter 15Making 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
...Starting Now