Sparse representations and compressive sensing for imaging and vision

Sparse representations and compressive sensing for imaging and vision

by Patel, Vishal M.

Type Book
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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 highli…

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Title Statements

  • Full title :Sparse representations and compressive sensing for imaging and vision / Vishal M. Patel, Rama Chellappa.

Summary

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.--[Source inconnue].

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Edition Statements

  • Publication Date:2013.

Publication Statements

  • Publisher(s):Springer
  • Place of Publication:Dordrecht
  • Language:eng
  • Publication Date:2013.

Notes

Titre de l'écran-titre (visionné le 12 mars 2013).

The Physical Object

  • Description:1 ressource en ligne (1 texte électronique (110 pages))

Edition Identifiers

  • ISBN:1461463815, 9781461463818
  • oclc:on1132010326
  • LC Classification:TK5102.9
  • Dewey Decimal:621.382

Table of Contents

Compressive Sensing -- Compressive Acquisition -- Compressive Sensing for Vision -- Sparse Representation-based Object Recognition -- Dictionary Learning -- Concluding Remarks.

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