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Compressed Sensing with Side Information on the Feasible Region

  • Mohammad┬áRostami

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Mohammed Rostami
    Pages 1-7
  3. Mohammed Rostami
    Pages 9-22

About this book

Introduction

This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing.

Keywords

Compressive Sensing Derivative Compressive Sampling Image Deblurring Inverse Problems Shack-Hartmann Interferometer Sparse Sampling

Authors and affiliations

  • Mohammad┬áRostami
    • 1
  1. 1.and DesignSingapore University of TechnologySingaporeSingapore

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-00366-5
  • Copyright Information The Author(s) 2013
  • Publisher Name Springer, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-319-00365-8
  • Online ISBN 978-3-319-00366-5
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • Buy this book on publisher's site
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