SpringerBriefs in Electrical and Computer Engineering

Sparse Representations and Compressive Sensing for Imaging and Vision

Authors: Patel, Vishal M., Chellappa, Rama

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  • ISBN 978-1-4614-6381-8
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About this book

Compressed sensing or compressive sensing is a new concept in signal processing where one measures a small number of non-adaptive linear combinations of the signal.  These measurements are usually much smaller than the number of samples that define the signal.  From these small numbers of measurements, the signal is then reconstructed by non-linear procedure.  Compressed sensing has recently emerged as a powerful tool for efficiently processing data in non-traditional ways.  In this book, we highlight some of the key mathematical insights underlying sparse representation and compressed sensing and illustrate the role of these theories in classical vision, imaging and biometrics problems.

Table of contents (7 chapters)

  • Introduction

    Patel, Vishal M. (et al.)

    Pages 1-2

  • Compressive Sensing

    Patel, Vishal M. (et al.)

    Pages 3-15

  • Compressive Acquisition

    Patel, Vishal M. (et al.)

    Pages 17-40

  • Compressive Sensing for Vision

    Patel, Vishal M. (et al.)

    Pages 41-61

  • Sparse Representation-based Object Recognition

    Patel, Vishal M. (et al.)

    Pages 63-84

Buy this book

eBook $29.99
price for USA (gross)
  • ISBN 978-1-4614-6381-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $39.95
price for USA
  • ISBN 978-1-4614-6380-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Sparse Representations and Compressive Sensing for Imaging and Vision
Authors
Series Title
SpringerBriefs in Electrical and Computer Engineering
Copyright
2013
Publisher
Springer-Verlag New York
Copyright Holder
The Author(s)
eBook ISBN
978-1-4614-6381-8
DOI
10.1007/978-1-4614-6381-8
Softcover ISBN
978-1-4614-6380-1
Series ISSN
2191-8112
Edition Number
1
Number of Pages
X, 102
Number of Illustrations and Tables
41 b/w illustrations
Topics