Variable Length Codes For Data Compression
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Variable-length Codes for Data Compression
Author: David Salomon
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-09-05
Most data compression methods that are based on variable-length codes employ the Huffman or Golomb codes. However, there are a large number of less-known codes that have useful properties and these can be useful. This book brings this large set of codes to the attention of workers in the field and for students of computer science. The author’s crystal clear style of writing and presentation allows easy access to the topic.
Data Compression
Author: David Salomon
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-05-09
Data compression is one of the most important fields and tools in modern computing. From archiving data, to CD ROMs, and from coding theory to image analysis, many facets of modern computing rely upon data compression. Data Compression provides a comprehensive reference for the many different types and methods of compression. Included are a detailed and helpful taxonomy, analysis of most common methods, and discussions on the use and comparative benefits of methods and description of "how to" use them. The presentation is organized into the main branches of the field of data compression: run length encoding, statistical methods, dictionary-based methods, image compression, audio compression, and video compression. Detailed descriptions and explanations of the most well-known and frequently used compression methods are covered in a self-contained fashion, with an accessible style and technical level for specialists and nonspecialists. Topics and features: coverage of video compression, including MPEG-1 and H.261; thorough coverage of wavelets methods, including CWT, DWT, EZW and the new Lifting Scheme technique; complete audio compression; QM coder used in JPEG and JBIG, including new JPEG 200 standard; image transformations and detailed coverage of discrete cosine transform and Haar transform; coverage of EIDAC method for compressing simple images; prefix image compression; ACB and FHM curve compression; geometric compression and edgebreaker technique. Data Compression provides an invaluable reference and guide for all computer scientists, computer engineers, electrical engineers, signal/image processing engineers and other scientists needing a comprehensive compilation for a broad range of compression methods.
Understanding Compression
Author: Colt McAnlis
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2016-07-13
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