Mohammad Rostami: Compressed Sensing with Side Information on the Feasible Region

Compressed Sensing with Side Information on the Feasible Region


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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Author: Mohammad Rostami
Number of Pages: 69 pages
Published Date: 03 Jun 2013
Publisher: Springer International Publishing AG
Publication Country: Cham, Switzerland
Language: English
ISBN: 9783319003658
Download Link: Click Here
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