9781491961537

9781491961506

1491961503

9781491961483

1491961481

1491961538

Copyright; Table of Contents; Foreword; Preface; How to Read This Book; How to Read This Book Backwards; Chapter Synopsis; Chapter 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; A World Built on Data Compression; Chapter 2. Do Not Skip This Chapter; Understanding Binary; Base 10 System; Binary Number System; Information Theory; An Excursion into Binary Search; Entropy: The Minimum Bits Needed to Represent a Number; Standard Number Lengths; Chapter 3. Breaking Entropy

Understanding EntropyWhat This Entropy Stuff Is Good For; Understanding Probability; Breaking Entropy; Example 1: Delta Coding; Example 2: Symbol Grouping; Example 3: Permutations; Information Theory Versus Data Compression; Chapter 4. Variable-Length Codes; Morse Code; Probability, Entropy, and Codeword Size; Variable-Length Codes; Using VLCs; Creating VLCs; A Handful of Example VLCs; Finding the Right Code for Your Data Set; Chapter 5. Statistical Encoding; Statistically Compressing to Entropy; Huffman Coding; Building a Huffman Tree; Generating Codewords; Encoding and Decoding

Practical ImplementationsArithmetic Coding; Finding the Right Number; Encoding; Picking the Right Output Value; Decoding; Practical Implementations; Asymmetric Numeral Systems; Encoding and Decoding Using a Transform Table; Creating the Reference Table; Using ANS for Compression; Decoding Example; So Where Does the Compression Come From?; Practical Compression: Which Statistical Algorithm Do I Choose?; Chapter 6. Adaptive Statistical Encoding; Locality Matters for Entropy; Adaptive VLC Encoding; Dynamically Building a VLC Table; Literals; Resets; Knowing When to Reset; Using This in Practice

Adaptive Arithmetic CodingAdaptive Huffman Coding; The Modern Choice; Chapter 7. Dictionary Transforms; A Basic Dictionary Transform; Finding the Right "Words"; The Lempel-Ziv Algorithm; How LZ Works; Encoding; Decoding; Compressing LZ output; LZ Variants; Collect Them All!; Chapter 8. Contextual Data Transforms; Run-Length Encoding; Dealing with Short Runs; Compressing; Delta Coding; XOR Delta Coding; Frame of Reference Delta Coding; Patched Frame of Reference Delta Coding; Compressing Delta-Encoded Data; Does It Work on Text?; Move-to-Front Coding; Avoiding Rogue Symbols; Compressing MTF

Burrows-Wheeler TransformOrdering Is Important!; How BWT Works; Inverse BWT; Practical Implementations; Compressing BWT; Chapter 9. Data Modeling; The Chains of Markov; Markov and Compression; Practical Implementations; Prediction by Partial Matching; The Search Trie; Compressing a Symbol; Choosing a Sensible N Value; Dealing with Unknown Symbols; Context Mixing; Types of Models; Types of Mixing; The Next Big Thing?; Chapter 10. Switching Gears; Media-Specific Compression; General-Purpose Compression; Compression in Practice; Chapter 11. Evaluating Compression; Compression Usage Scenarios

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