May 1, 2024
Updated May 9, 2025
26 minute read
Data compression is the process of encoding information using fewer bits than the original representation. At its core, it's about making data smaller. This is achieved by identifying and eliminating statistical redundancy in data. Think of it like creating a shorthand for frequently used phrases; instead of writing out the full phrase each time, you use the shorthand, saving space and effort. Data compression is a fundamental concept in computer science and data management, playing a crucial role in how we store, transmit, and process information in the digital world.
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Reading list
We've selected 28 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Compression.
Provides a comprehensive introduction to data compression, covering both the theoretical foundations and the practical implementation of compression algorithms. It is written in a clear and concise style, and includes numerous examples and exercises.
Comprehensive guide to data compression, covering both the theoretical foundations and the practical implementation of compression algorithms. It is written in a clear and concise style, and includes numerous examples and exercises.
Provides a comprehensive introduction to data compression, covering the fundamentals of the field and a wide range of compression techniques. It is written in a clear and concise style, and includes numerous examples and exercises.
Offers a more accessible approach to data compression, focusing on practical understanding for developers. It explains how algorithms work with less emphasis on complex mathematics, making it a good starting point for those with a programming background. It helps in choosing appropriate compression tools for various applications.
Focuses specifically on compression techniques for images and video, which are crucial in multimedia applications. It covers fundamental principles, algorithms, and relevant standards (like JPEG and MPEG). It is essential for those interested in the application of compression in multimedia engineering.
A classic in the field, this book provides a solid introduction to data compression algorithms with a focus on practical implementation in C. It covers essential lossless and lossy algorithms and is valuable for understanding the core concepts and building foundational knowledge. While older, the fundamental principles remain relevant, making it a useful reference for programmers.
Edited by Khalid Sayood, this handbook offers a collection of chapters on various lossless compression techniques written by experts in the field. It provides in-depth coverage of specific algorithms and their nuances, making it a valuable reference for researchers and practitioners focused on lossless methods.
Provides a comprehensive overview of data compression from a reference perspective, covering a wide range of compression techniques and their applications. It is written in a clear and concise style, and includes numerous examples and exercises.
Another specialized book by Khalid Sayood, this text focuses specifically on the principles and techniques of digital image compression. It covers various image compression standards and algorithms in detail, making it ideal for those concentrating on image processing.
Understanding data compression requires a strong foundation in information theory. seminal work in the field, providing the necessary mathematical and theoretical background to comprehend the limits and possibilities of compression. It is essential reading for anyone seeking a deep understanding of the subject, particularly at the graduate level and beyond.
Provides a comprehensive overview of data compression from a theoretical perspective, covering a wide range of compression techniques and their applications. It is written in a clear and concise style, and includes numerous examples and exercises.
Provides a comprehensive overview of data compression from a professional perspective, covering a wide range of compression techniques and their applications. It is written in a clear and concise style, and includes numerous examples and exercises.
Provides a theoretical foundation for data compression, covering the mathematical principles behind compression algorithms. It is written in a clear and concise style, and includes numerous examples and exercises.
As the title suggests, this book offers a concise introduction to data compression. It's a good option for those who need a quicker overview of the fundamental concepts and algorithms without the extensive detail found in larger reference books. It can serve as a good starting point before diving into more comprehensive texts.
Provides a comprehensive overview of data compression algorithms and techniques, covering a wide range of compression techniques and their applications. It is written in a clear and concise style, and includes numerous examples and exercises.
Provides a theoretical foundation for data compression, exploring the underlying principles and mathematical concepts. It is suitable for readers who want to understand the 'why' behind compression algorithms and good complement to more practical guides. It is more theoretically oriented than 'Data Compression: The Complete Reference' by the same author.
Delves into the specifics of audio and voice compression, particularly in the context of communication systems. It covers the history, techniques, and standards used for compressing audio signals. It specialized book valuable for those focusing on audio processing and communication.
Provides an introduction to both information theory and data compression, highlighting the close relationship between the two fields. It is suitable for students seeking to understand the theoretical basis of compression and its connection to information theory.
Approaches data compression from a more mathematical perspective, connecting it to areas like spectral methods and wavelets. It is suitable for those with a strong mathematical background interested in the theoretical underpinnings and advanced techniques used in areas like image compression.
Detailed exploration of vector quantization, a key technique in lossy data compression, particularly for speech and image signals. It's a specialized topic requiring a solid understanding of signal processing and is suitable for advanced students and researchers.
Provides a broad perspective on managing large datasets, with a significant focus on compression and indexing techniques for text and images. It is valuable for understanding how compression is applied in the context of information retrieval and database systems. While older, the core concepts on compression within this domain remain pertinent.
Offers a very visual and easy-to-understand introduction to algorithms, including a section on data compression. It's an excellent starting point for beginners or those who prefer a less mathematical approach to grasping algorithmic concepts relevant to compression.
Takes a practical approach to explaining compression algorithms, focusing on how they work and how to implement them. It is geared towards programmers who want to understand the code behind compression techniques. While some algorithms might be older, the practical insights are valuable.
For more information about how these books relate to this course, visit:
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