Description

Book Synopsis

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

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

Compressive Sensing of Earth Observations

Product form

£166.25

Includes FREE delivery

RRP £175.00 – you save £8.75 (5%)

Order before 4pm today for delivery by Thu 18 Dec 2025.

A Hardback by C.H. Chen

1 in stock


    View other formats and editions of Compressive Sensing of Earth Observations by C.H. Chen

    Publisher: Taylor & Francis Inc
    Publication Date: 01/06/2017
    ISBN13: 9781498774376, 978-1498774376
    ISBN10: 1498774377

    Description

    Book Synopsis

    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

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

    Recently viewed products

    © 2025 Book Curl

      • American Express
      • Apple Pay
      • Diners Club
      • Discover
      • Google Pay
      • Maestro
      • Mastercard
      • PayPal
      • Shop Pay
      • Union Pay
      • Visa

      Login

      Forgot your password?

      Don't have an account yet?
      Create account