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Compressive Sensing of Earth Observations

Edited by: C.H. Chen

Print publication date:  June  2017
Online publication date:  May  2017

Print ISBN: 9781498774376
eBook ISBN: 9781315154626
Adobe ISBN:

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Book description

Future remote sensing systems will make extensive use of Compressive Sensing (CS) as it becomes more integrated into the system design with increased high resolution sensor developments and the rising earth observation data generated each year. Written by leading experts in the field Compressive Sensing of Earth Observations provides a comprehensive and balanced coverage of the theory and applications of CS in all aspects of earth observations. This work covers a myriad of practical aspects such as the use of CS in detection of human vital signs in a cluttered environment and the corresponding modeling of rib-cage breathing. Readers are also presented with three different applications of CS to the ISAR imaging problem, which includes image reconstruction from compressed data, resolution enhancement, and image reconstruction from incomplete data.

Table of contents

Prelims Download PDF
Chapter  1:  Compressed Sensing: From Theory to Praxis Download PDF
Chapter  2:  Compressive Sensing on the Sphere: Slepian Functions for Applications in Geophysics Download PDF
Chapter  3:  Compressive Sensing–Based High-Resolution Imaging and Tracking of Targets and Human Vital Sign Detection behind Walls Download PDF
Chapter  4:  Recovery Guarantees for High-Resolution Radar Sensing with Compressive Illumination Download PDF
Chapter  5:  Compressive Sensing for Inverse Synthetic Aperture Radar Imaging Download PDF
Chapter  6:  A Novel Compressed Sensing–Based Algorithm for Space–Time Signal Processing Using Airborne Radars Download PDF
Chapter  7:  Bayesian Sparse Estimation of Radar Targets in the Compressed Sensing Framework Download PDF
Chapter  8:  Virtual Experiments and Compressive Sensing for Subsurface Microwave Tomography Download PDF
Chapter  9:  Seismic Source Monitoring with Compressive Sensing Download PDF
Chapter  10:  Seismic Data Regularization and Imaging Based on Compressive Sensing and Sparse Optimization Download PDF
Chapter  11:  Land Use Classification with Sparse Models Download PDF
Chapter  12:  Compressive Sensing for Reconstruction, Classification, and Detection of Hyperspectral Images Download PDF
Chapter  13:  Structured Abundance Matrix Estimation for Land Cover Hyperspectral Image Unmixing Download PDF
Chapter  14:  Parallel Coded Aperture Method for Hyperspectral Compressive Sensing on GPU Download PDF
Chapter  15:  Algorithms and Prototyping of a Compressive Hyperspectral Imager Download PDF
Index Download PDF
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