Hyperspectral Data Compression

By: Giovanni Motta (Editor), Francesco Rizzo (Editor), James A. Storer (Editor)

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Hardcover | 1 November 2005

At a Glance

Hardcover
432 Pages

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23.5 x 15.88 x 1.91

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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.

Industry Reviews

From the reviews:

"Motta, Rizzo, and Storer ... are veterans in the field of data compression, both individually and collaboratively. They bring together a concentrated set of contributed papers, focusing on compressing hyperspectral (multidimensional) data. ... This compendium describes cutting-edge compression technology, and is sure to occupy an important position in the current literature of the field. The editors have accomplished their goal of making this technology available to the educational and industrial communities." (R. Goldberg, Computing Reviews, Vol. 50 (1), January, 2009)

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You Can Find This Book In

Non-Fiction Earth Sciences, Geography, Environment, Planning Geography Geographical Information Systems GIS & Remote Sensing Computing & I.T.Computer Science Image Processing Engineering & Technology Other Technologies & Applied Sciences Applied Optics Graphical & Digital Media Applications Databases

Information Retrieval Artificial Intelligence Computer Vision

"An Architecture for the Compression of Hyperspectral Imagery"	p. 1
"Lossless Predictive Compression of Hyperspectral Images"	p. 35
"Lossless Hyperspectral Image Compression via Linear Prediction"	p. 57
"Lossless Compression of Ultraspectral Sounder Data"	p. 75
"Locally Optimal Partitioned Vector Quantization of Hyperspectral Data"	p. 107
"Near-Lossless Compression of Hyperspectral Imagery Through Crisp/Fuzzy Adaptive DPCM"	p. 147
"Joint Classification and Compression of Hyperspectral Images"	p. 179
"Predictive Coding of Hyperspectral Images"	p. 197
"Coding of Hyperspectral Imagery with Trellis-Coded Quantization"	p. 233
"Three-Dimensional Wavelet-Based Compression of Hyperspectral Images"	p. 273
"Spectral/Spatial Hyperspectral Image Compression"	p. 309
"Compression of Earth Science Data with JPEG2000"	p. 347
"Spectral Ringing Artifacts in Hyperspectral Image Data Compression"	p. 379
Table of Contents provided by Ingram. All Rights Reserved.

Hyperspectral Data Compression

At a Glance

Hardcover

Industry Reviews

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How to return your order

Defective items

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