DocumentCode
3731746
Title
Superresolution without separation
Author
Geoffrey Schiebinger;Elina Robeva;Benjamin Recht
Author_Institution
Deparment of Statistics, University of California, Berkeley, USA
fYear
2015
Firstpage
45
Lastpage
48
Abstract
This paper provides a theoretical analysis of diffraction-limited superresolution, demonstrating that arbitrarily close point sources can be resolved in ideal situations. Precisely, we assume that the incoming signal is a linear combination of M shifted copies of a known waveform with unknown shifts and amplitudes, and one only observes a finite collection of evaluations of this signal. We characterize properties of the base waveform such that the exact translations and amplitudes can be recovered from 2M + 1 observations. This recovery is achieved by solving a a weighted version of basis pursuit over a continuous dictionary. Our methods combine classical polynomial interpolation techniques with contemporary tools from compressed sensing.
Keywords
"Signal resolution","Spatial resolution","Imaging","Conferences","Interpolation","Optimization"
Publisher
ieee
Conference_Titel
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015 IEEE 6th International Workshop on
Type
conf
DOI
10.1109/CAMSAP.2015.7383732
Filename
7383732
Link To Document