Compressed Sensing with Side Information on the Feasible Region. Questo articolo non è disponibile.
Lingua: inglese
Editore: Springer, 2013
Serie: Libro 36 di 209 - SpringerBriefs in Electrical and Computer Engineering
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Compressed Sensing with Side Information on the Feasible Region | Mohammad Rostami | Taschenbuch | SpringerBriefs in Electrical and Computer Engineering | xiii | Englisch | 2013 | Springer | EAN 9783319003658 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Codice articolo 105926183
- Titolo
- Compressed Sensing with Side Information on the Feasible Region
- Autore
- Mohammad Rostami
- Editore
- Springer
- Anno di pubblicazione
- 2013
- Condizione
- Neu
- Rilegatura
- Taschenbuch
- Lingua
- inglese
- ISBN 10
- 3319003658
- ISBN 13
- 9783319003658
- Peso dell'articolo
- 143 grammi
- Dimensioni
- 235 x 155 x 6 mm
- Serie
- Libro 36 di 209: SpringerBriefs in Electrical and Computer Engineering
- Cataloghi dei venditori
- Bücher
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.
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Informazioni sull’autore
Mohammad Rostami,
Singapore University of Technology and Design,
20 Dover Drive,
Singapore 138682
e-mail: m2rostam@uwaterloo.ca
Singapore University of Technology and Design,
20 Dover Drive,
Singapore 138682
e-mail: m2rostam@uwaterloo.ca
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