DocumentCode :
1662071
Title :
Compressive template matching on multispectral data
Author :
Rousseau, Sylvain ; Helbert, David ; Carre, Philippe ; Blanc-Talon, Jacques
Author_Institution :
XLIM, Univ. of Poitiers, Futuroscope Chasseneuil, France
fYear :
2013
Firstpage :
2386
Lastpage :
2389
Abstract :
This paper adapts a new template matching and target detection algorithm in multispectral images to a compressive sensing strategy. That template matching algorithm found in [1] relies on particular properties of L1 minimization algorithms to succeed. We propose a new algorithm that is reconstructing in a single step the location of a given signature of interest bypassing the image reconstruction and the template matching algorithm on that image. For that purpose, we use a modified split Bregman algorithm with various regularizers. We conduct numerical experiments on real-world multispectral image.
Keywords :
image matching; image reconstruction; minimisation; compressive sensing strategy; compressive template matching; image reconstruction; minimization algorithms; modified split Bregman algorithm; multispectral data; multispectral images; target detection algorithm; Compressed sensing; Image coding; Image reconstruction; Imaging; Minimization; Sensors; TV; Bregman; compressed sensing; multispectral image; template matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6638082
Filename :
6638082
Link To Document :
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