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Compressed sensing with side information on the feasible region

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...

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Detalles Bibliográficos
Autor principal: Rostami, Mohammad
Lenguaje:eng
Publicado: Springer 2013
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-00366-5
http://cds.cern.ch/record/1555615
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author Rostami, Mohammad
author_facet Rostami, Mohammad
author_sort Rostami, Mohammad
collection CERN
description 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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spelling cern-15556152021-04-21T22:37:12Zdoi:10.1007/978-3-319-00366-5http://cds.cern.ch/record/1555615engRostami, MohammadCompressed sensing with side information on the feasible regionEngineeringThis 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.Springeroai:cds.cern.ch:15556152013
spellingShingle Engineering
Rostami, Mohammad
Compressed sensing with side information on the feasible region
title Compressed sensing with side information on the feasible region
title_full Compressed sensing with side information on the feasible region
title_fullStr Compressed sensing with side information on the feasible region
title_full_unstemmed Compressed sensing with side information on the feasible region
title_short Compressed sensing with side information on the feasible region
title_sort compressed sensing with side information on the feasible region
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-00366-5
http://cds.cern.ch/record/1555615
work_keys_str_mv AT rostamimohammad compressedsensingwithsideinformationonthefeasibleregion