Details

Hyperspectral Data Compression

Hyperspectral Data Compression



von: Giovanni Motta, Francesco Rizzo, James A. Storer

149,79 €

Verlag: Springer
Format: PDF
Veröffentl.: 03.06.2006
ISBN/EAN: 9780387286006
Sprache: englisch
Anzahl Seiten: 418

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Beschreibungen

Titelbeschreibung

<STRONG>Hyperspectral Data Compression </STRONG>provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery.&nbsp;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).&nbsp;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.&nbsp;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.&nbsp;Chapter 13 examines artifacts that can arise from lossy compression.

Inhaltsverzeichnis

An Architecture for the Compression of Hyperspectral Imagery.- Lossless Predictive Compression of Hyperspectral Images.- Lossless Hyperspectral Image Compression via Linear Prediction.- Lossless Compression of Ultraspectral Sounder Data.- Locally Optimal Partitioned Vector Quantization of Hyperspectral Data.- Near-Lossless Compression of Hyperspectral Imagery Through Crisp/Fuzzy Adaptive DPCM.- Joint Classification and Compression of Hyperspectral Images.- Predictive Coding of Hyperspectral Images.- Coding of Hyperspectral Imagery with Trellis-Coded Quantization.- Three-Dimensional Wavelet-Based Compression of Hyperspectral Images.- Spectral/Spatial Hyperspectral Image Compression.- Compression of Earth Science Data with JPEG2000.- Spectral Ringing Artifacts in Hyperspectral Image Data Compression.

Autorenportrait

James A. Storer is Chair of the IEEE Data Compression Conference.

Back cover copy

HYPERSPECTRAL DATA COMPRESSION&nbsp;presents the most recent results in the field of compression of remote sensing 3D data, with a focus on multispectral and hyperspectral imagery.&nbsp; This book is essential for researchers working&nbsp;across related&nbsp;fields including: multi-dimensional data compression,&nbsp;multispectral and hyperspectral data archives,&nbsp;&nbsp;remote sensing, scientific image processing, military and aerospace image processing, image segmentation, image classification, and target detection.&nbsp;

Sonderbeitrag

An excellent technical reference for both academic and industrial researchers in the fields of computer science and engineering A compilation of the most current results in the field of compression of remote sensing 3D data with chapters contributed by leading researchers in the area The only book currently on the market which focuses on the newest areas of research: multispectral and hyperspectral imagery Includes supplementary material: sn.pub/extras

Verkaufsargumente

<P>Interest in remote sensing applications and platforms has grown dramatically in recent years. This leading-edge reference surveys the latest results in the field of compression of remote sensing 3D data, with a focus on hyperspectral imagery. Unique in scope in this emerging research area, the book will be essential for industrial and academic researchers working in the fields of multi-dimensional data compression, remote sensing, military and aerospace image processing, homeland security, archival of large volumes of scientific and medical data, image classification, and target detection.</P>