Hyperspectral Data Compression / edited by Giovanni Motta, Francesco Rizzo, James A. Storer.

Springer eBooks

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.

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

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