Hyperspectral Data Compression / Edition 1

Hyperspectral Data Compression / Edition 1

by Giovanni Motta
     
 

ISBN-10: 0387285792

ISBN-13: 9780387285795

Pub. Date: 11/17/2005

Publisher: Springer US

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

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Overview

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

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Product Details

ISBN-13:
9780387285795
Publisher:
Springer US
Publication date:
11/17/2005
Edition description:
2006
Pages:
418
Product dimensions:
6.14(w) x 9.25(h) x 0.04(d)

Table of Contents

Ch. 1An architecture for the compression of hyperspectral imagery1
Ch. 2Lossless predictive compression of hyperspectral images35
Ch. 3Lossless hyperspectral image compression via linear prediction57
Ch. 4Lossless compression of ultraspectral sounder data75
Ch. 5Locally optimal partitioned vector quantization of hyperspectral data107
Ch. 6Near-lossless compression of hyperspectral imagery through crisp/fuzzy adaptive DPCM147
Ch. 7Joint classification and compression of hyperspectral images179
Ch. 8Predictive coding of hyperspectral images197
Ch. 9Coding of hyperspectral imagery with trellis-coded quantization233
Ch. 10Three-dimensional wavelet-based compression of hyperspectral images273
Ch. 11Spectral/spatial hyperspectral image compression309
Ch. 12Compression of Earth science data with JPEG2000347
Ch. 13Spectral ringing artifacts in hyperspectral image data compression379

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