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Automatic target recognition based on simultaneous sparse representation

9 years 9 months ago
Automatic target recognition based on simultaneous sparse representation
In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extraction. The dictionary learning algorithm is based on class supervised simultaneous orthogonal matching pursuit while a matching pursuit-based similarity measure is used for classification. We show how the proposed framework can be helpful for efficient utilization of data, with the possibility of developing real-time, robust target classification. We verify the efficacy of the proposed algorithm using confusion matrices on the well known Comanche forward-looking infrared data set consisting of ten different military targets at different orientations.
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellap
Added 03 Mar 2011
Updated 03 Mar 2011
Type Journal
Year 2010
Where ICIP
Authors Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellappa
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