Sparsity-motivated automatic target recognition

被引：33
作者：
Patel, Vishal M. [1 ]
Nasrabadi, Nasser M. [2 ]
Chellappa, Rama [1 ]
机构：
[1] Univ Maryland, Dept Elect & Comp Engn, Ctr Automat Res, College Pk, MD 20742 USA
[2] US Army Res Lab, Adelphi, MD 20783 USA
来源：
APPLIED OPTICS | 2011年 / 50卷 / 10期
关键词：
SIGNAL RECOVERY; BASIS PURSUIT; ATOMIC DECOMPOSITION; MATCHING PURSUIT; REGRESSION; SELECTION; LASSO;
D O I：
10.1364/AO.50.001425
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
We present an automatic target recognition algorithm using the recently developed theory of sparse representations and compressive sensing. We show how sparsity can be helpful for efficient utilization of data for target recognition. We verify the efficacy of the proposed algorithm in terms of the recognition rate and confusion matrices on the well known Comanche (Boeing-Sikorsky, USA) forward-looking IR data set consisting of ten different military targets at different orientations. (C) 2011 Optical Society of America
引用
收藏
页码：1425 / 1433
页数：9
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