DocumentCode :
1790555
Title :
Innovative CS imaging methods in transformed domains
Author :
Moriyama, Takumi ; Anselmi, Nicola ; Oliveri, G. ; Massa, A.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Nagasaki, Nagasaki, Japan
fYear :
2014
fDate :
16-19 Nov. 2014
Firstpage :
1
Lastpage :
3
Abstract :
The solution of linear microwave imaging problems is considered in this work through innovative classes of Compressive Sensing (CS) methods. More in detail, the formulation of the inversion process in transformed domains with sparseness-regularized formulations is considered. Representative numerical examples illustrating the potentialities and limitations of the arising CS inversion approaches are reported.
Keywords :
compressed sensing; image representation; microwave imaging; transforms; compressive sensing method; innovative CS imaging methods; inversion process formulation; linear microwave imaging problems; sparseness-regularized formulations; transformed domains; Antennas; Bayes methods; Compressed sensing; Image reconstruction; Microwave imaging; Wavelet domain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Antenna Measurements & Applications (CAMA), 2014 IEEE Conference on
Conference_Location :
Antibes Juan-les-Pins
Type :
conf
DOI :
10.1109/CAMA.2014.7003312
Filename :
7003312
Link To Document :
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