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Giovanni Motta & Francesco Rizzo 
Hyperspectral Data Compression 

समर्थन
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.
€149.79
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विषयसूची

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.

लेखक के बारे में

James A. Storer is Chair of the IEEE Data Compression Conference.
भाषा अंग्रेज़ी ● स्वरूप PDF ● पेज 418 ● ISBN 9780387286006 ● फाइल का आकार 47.7 MB ● संपादक Giovanni Motta & Francesco Rizzo ● प्रकाशक Springer US ● शहर NY ● देश US ● प्रकाशित 2006 ● डाउनलोड करने योग्य 24 महीने ● मुद्रा EUR ● आईडी 2144483 ● कॉपी सुरक्षा सामाजिक DRM

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