DocumentCode :
1734137
Title :
Super-resolution by compressive sensing algorithms
Author :
Fannjiang, A. ; Wenjing Liao
Author_Institution :
Dept. of Math., UC Davis, Davis, CA, USA
fYear :
2012
Firstpage :
411
Lastpage :
415
Abstract :
In this work, super-resolution by 4 compressive sensing methods (OMP, BP, BLOOMP, BP-BLOT) with highly coherent partial Fourier measurements is comparatively studied. An alternative metric more suitable for gauging the quality of spike recovery is introduced and based on the concept of filtration with a parameter representing the level of tolerance for support offset. In terms of the filtered error norm only BLOOMP and BP-BLOT can perform grid-independent recovery of well separated spikes of Rayleigh index 1 for arbitrarily large superresolution factor. Moreover both BLOOMP and BP-BLOT can localize spike support within a few percent of the Rayleigh length. This is a weak form of super-resolution. Only BP-BLOT can achieve this feat for closely spaced spikes separated by a fraction of the Rayleigh length, a strong form of superresolution.
Keywords :
compressed sensing; signal resolution; BLOOMP; BP-BLOT; Rayleigh index; Rayleigh length; coherent partial Fourier measurements; compressive sensing algorithms; filtration; grid-independent recovery; spike recovery quality; super-resolution; superresolution factor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
978-1-4673-5050-1
Type :
conf
DOI :
10.1109/ACSSC.2012.6489036
Filename :
6489036
Link To Document :
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