Introduction to Data Compression
Each edition of Introduction to Data Compression has widely been considered the best introduction and reference text on the art and science of data compression, and the third edition continues in this tradition. Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio, and video. The third edition includes all the cutting edge updates the reader will need during the work day and in class.
Khalid Sayood provides an extensive introduction to the theory underlying today's compression techniques with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression Introduction to Data Compression, includes lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization. Khalid Sayood provides a working knowledge of data compression, giving the reader the tools to develop a complete and concise compression package upon completion of his book.
*New content added on the topic of audio compression including a description of the mp3 algorithm *New video coding standard and new facsimile standard explained *Completely explains established and emerging standards in depth including JPEG 2000, JPEG-LS, MPEG-2, Group 3 and 4 faxes, JBIG 2, ADPCM, LPC, CELP, and MELP *Source code provided via companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own applications
Why Read This Book
You will get a single, accessible reference that explains both the theory (entropy, rate-distortion, quantization) and practical algorithms (Huffman, arithmetic, LZ, DCT, wavelets) used in modern multimedia compression. The book balances math and worked examples so you can understand why algorithms work and how to implement or choose them for audio, speech, image, and video problems.
Who Will Benefit
DSP engineers, multimedia systems designers, and graduate students who need a practical yet theoretical grounding in compression methods for audio, speech, image, and video applications.
Level: Intermediate — Prerequisites: Undergraduate-level signals and systems and basic probability/statistics; comfort with linear algebra and discrete-time signal concepts for transform-based compression.
Key Takeaways
- Implement core lossless coders such as Huffman and arithmetic coding and understand their trade-offs.
- Apply predictive and transform coding techniques (DCT and wavelets) to design lossy compression systems.
- Analyze rate-distortion behavior and design quantizers to meet bitrate and quality targets.
- Explain and implement common standards-level techniques used in JPEG, MPEG, MP3/AAC and speech codecs (basic CELP principles).
- Evaluate trade-offs between modeling, entropy coding, and complexity for real-world multimedia compression.
Topics Covered
- Introduction and Motivation; Overview of Compression Applications
- Information Theory Foundations: Entropy and Mutual Information
- Lossless Compression: Huffman and Arithmetic Coding
- Dictionary Methods and Lempel-Ziv Algorithms
- Statistical Modeling and Context-Based Coding
- Quantization: Scalar and Vector Quantization, Uniform and Nonuniform
- Predictive Coding and Linear Predictors
- Transform Coding: DCT, KLT and Subband Methods
- Wavelet-Based Compression and Embedded Coding
- Image Compression: JPEG and JPEG2000
- Audio and Speech Coding: Perceptual Coding, MP3/AAC, Speech Coders (CELP)
- Video Compression Basics: Motion Compensation and MPEG Family
- Rate-Distortion Theory and Practical Bit Allocation
- Practical Issues, Standards, and Implementation Considerations
- Appendices and Example Algorithms
Languages, Platforms & Tools
How It Compares
Covers much the same practical breadth as David Salomon's Data Compression: The Complete Reference but is more textbook-oriented with classroom examples; for deeper information-theoretic proofs pair it with Cover & Thomas's Elements of Information Theory.
