Paper Info
Title
The Restricted Isometry Property of the Radon-like CS matrix.
Abstract
In compressive sensing, the Restricted Isometry Property is an analytical condition on the measurement matrix that assures reconstruction of a signal which is sparse either in the spatial or in a transformed domain given an undersampled measurements' set. In this paper, we demonstrate the RIP for a sparse, structured measurements matrix, referred to as Radon-like CS matrix. The sparse Radon-Like CS matrix favorably applies to real sensing problems, since it significantly reduces the energy/bandwidth cost of actually collecting each and every sensed values contributing to the CS measurements. Simulation results confirm the feasibility of field reconstruction from undersampled CS measurements set obtained using the Radon-Like CS matrix.
Year
DOI
Venue
2013
10.1109/MMSP.2013.6659296
MMSP
Keywords
Field
DocType
Radon transforms,compressed sensing,image reconstruction,matrix algebra,CS measurements,RIP,Radon-like CS matrix,compressive sensing,energy-bandwidth cost,restricted isometry property,signal reconstruction,structured measurement matrix
Iterative reconstruction,Computer vision,Matrix (mathematics),Matrix algebra,Computer science,Radon,Algorithm,Bandwidth (signal processing),Artificial intelligence,Geometry,Compressed sensing,Restricted isometry property
Conference
ISSN
Citations 
PageRank 
2163-3517
3
0.42
References 
Authors
8
4
Name
Order
Citations
PageRank
Stefania Colonnese113726.43
Stefano Rinauro2508.72
Roberto Cusani316833.10
Gaetano Scarano420931.32