What is Data Compression In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Data compression Chapter 2: Audio file format Chapter 3: Codec Chapter 4: JPEG Chapter 5: Lossy compression Chapter 6: Lossless compression Chapter 7: Image compression Chapter 8: Transform coding Chapter 9: Video codec Chapter 10: Discrete cosine transform (II) Answering the public top questions about data compression. (III) Real world examples for the usage of data compression in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Data Compression.

THE DATA COMPRESSION MCQ (MULTIPLE CHOICE QUESTIONS) SERVES AS A VALUABLE RESOURCE FOR INDIVIDUALS AIMING TO DEEPEN THEIR UNDERSTANDING OF VARIOUS COMPETITIVE EXAMS, CLASS TESTS, QUIZ COMPETITIONS, AND SIMILAR ASSESSMENTS. WITH ITS EXTENSIVE COLLECTION OF MCQS, THIS BOOK EMPOWERS YOU TO ASSESS YOUR GRASP OF THE SUBJECT MATTER AND YOUR PROFICIENCY LEVEL. BY ENGAGING WITH THESE MULTIPLE-CHOICE QUESTIONS, YOU CAN IMPROVE YOUR KNOWLEDGE OF THE SUBJECT, IDENTIFY AREAS FOR IMPROVEMENT, AND LAY A SOLID FOUNDATION. DIVE INTO THE DATA COMPRESSION MCQ TO EXPAND YOUR DATA COMPRESSION KNOWLEDGE AND EXCEL IN QUIZ COMPETITIONS, ACADEMIC STUDIES, OR PROFESSIONAL ENDEAVORS. THE ANSWERS TO THE QUESTIONS ARE PROVIDED AT THE END OF EACH PAGE, MAKING IT EASY FOR PARTICIPANTS TO VERIFY THEIR ANSWERS AND PREPARE EFFECTIVELY.

Following an exchange of correspondence, I met Ross in Adelaide in June 1988. I was approached by the University of Adelaide about being an external examiner for this dissertation and willingly agreed. Upon receiving a copy of this work, what struck me most was the scholarship with which Ross approaches and advances this relatively new field of adaptive data compression. This scholarship, coupled with the ability to express himself clearly using figures, tables, and incisive prose, demanded that Ross's dissertation be given a wider audience. And so this thesis was brought to the attention of Kluwer. The modern data compression paradigm furthered by this work is based upon the separation of adaptive context modelling, adaptive statistics, and arithmetic coding. This work offers the most complete bibliography on this subject I am aware of. It provides an excellent and lucid review of the field, and should be equally as beneficial to newcomers as to those of us already in the field.

A comprehensive reference for the many different types and methods of compression, including a detailed and helpful taxonomy, an analysis of the most common methods, and discussions on their use and comparative benefits. The presentation is organized into the main branches of the field: 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 methods are covered in a self-contained fashion, with an accessible style and technical level for specialists and nonspecialists. In short, the book 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.

Hyperspectral Data Compression provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery. Chapter 1 addresses compression architecture, and reviews and compares compression methods. Chapters 2 through 4 focus on lossless compression (where the decompressed image must be bit for bit identical to the original). Chapter 5, contributed by the editors, describes a lossless algorithm based on vector quantization with extensions to near lossless and possibly lossy compression for efficient browning and pure pixel classification. Chapter 6 deals with near lossless compression while. Chapter 7 considers lossy techniques constrained by almost perfect classification. Chapters 8 through 12 address lossy compression of hyperspectral imagery, where there is a tradeoff between compression achieved and the quality of the decompressed image. Chapter 13 examines artifacts that can arise from lossy compression.

Satellite Data Compression covers recent progress in compression techniques for multispectral, hyperspectral and ultra spectral data. A survey of recent advances in the fields of satellite communications, remote sensing and geographical information systems is included. Satellite Data Compression, contributed by leaders in this field, is the first book available on satellite data compression. It covers onboard compression methodology and hardware developments in several space agencies. Case studies are presented on recent advances in satellite data compression techniques via various prediction-based, lookup-table-based, transform-based, clustering-based, and projection-based approaches. This book provides valuable information on state-of-the-art satellite data compression technologies for professionals and students who are interested in this topic. Satellite Data Compression is designed for a professional audience comprised of computer scientists working in satellite communications, sensor system design, remote sensing, data receiving, airborne imaging and geographical information systems (GIS). Advanced-level students and academic researchers will also benefit from this book.

Introduction to Data Compression, Third Edition, is a concise and comprehensive guide to data compression. This book introduces the reader 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, it covers lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization. It includes all the cutting edge updates the reader will need during the work day and in class. This edition adds new content on the topic of audio compression including a description of the mp3 algorithm, along with a new video coding standard and new facsimile standard explained. It explains in detail 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 is provided via a companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own applications. This book will appeal to professionals, software and hardware engineers, students, and to anyone interested in digital libraries and multimedia. *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

Abstract: This workshop explored promising computational approaches for handling the collection, ingestion, archival and retrieval of large quantities of data in future Earth and space science missions. It consisted of eleven presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application.

Abstract: This workshop explored promising computational approaches for handling the collection, ingestion, archival and retrieval of large quantities of data in future Earth and space science missions. It consisted of fourteen presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application.