Hyperspectral Data Compression
Hyperspectral Data Compression

Author: Giovanni Motta

Publisher: Springer Science & Business Media

Published: 2006-06-03

Total Pages: 422

ISBN-13: 0387286004

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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.

Advanced Concepts for Intelligent Vision Systems
Advanced Concepts for Intelligent Vision Systems

Author: Jacques Blanc-Talon

Publisher: Springer

Published: 2010-12-06

Total Pages: 397

ISBN-13: 3642176917

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This book constitutes the refereed proceedings of the 12th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2010, held in Changchun, China, in August 2010. The 78 revised full papers presented were carefully reviewed and selected from 144 submissions. The papers are organized in topical sections on image processing and analysis; segmentation and edge detection; 3D and depth; algorithms and optimizations; video processing; surveillance and camera networks; machine vision; remote sensing; and recognition, classification and tracking.

Satellite Data Compression
Satellite Data Compression

Author: Bormin Huang

Publisher: Springer Science & Business Media

Published: 2011-11-25

Total Pages: 312

ISBN-13: 1461411831

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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.

Document and Image Compression
Document and Image Compression

Author: Mauro Barni

Publisher: CRC Press

Published: 2018-10-08

Total Pages: 456

ISBN-13: 1420018833

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Although it's true that image compression research is a mature field, continued improvements in computing power and image representation tools keep the field spry. Faster processors enable previously intractable compression algorithms and schemes, and certainly the demand for highly portable high-quality images will not abate. Document and Image Compression highlights the current state of the field along with the most probable and promising future research directions for image coding. Organized into three broad sections, the book examines the currently available techniques, future directions, and techniques for specific classes of images. It begins with an introduction to multiresolution image representation, advanced coding and modeling techniques, and the basics of perceptual image coding. This leads to discussions of the JPEG 2000 and JPEG-LS standards, lossless coding, and fractal image compression. New directions are highlighted that involve image coding and representation paradigms beyond the wavelet-based framework, the use of redundant dictionaries, the distributed source coding paradigm, and novel data-hiding techniques. The book concludes with techniques developed for classes of images where the general-purpose algorithms fail, such as for binary images and shapes, compound documents, remote sensing images, medical images, and VLSI layout image data. Contributed by international experts, Document and Image Compression gathers the latest and most important developments in image coding into a single, convenient, and authoritative source.

Data Compression
Data Compression

Author: David Salomon

Publisher: Springer Science & Business Media

Published: 2006-05-09

Total Pages: 912

ISBN-13: 0387218327

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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.