Sparsity-motivated automatic target recognition

Vishal M. Patel; Nasser M. Nasrabadi; Rama Chellappa

doi:10.1364/AO.50.001425

Sparsity-motivated automatic target recognition

Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellappa

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	1425-1433
Number of pages	9
Journal	Applied Optics
Volume	50
Issue number	10
DOIs	https://doi.org/10.1364/AO.50.001425
State	Published - Apr 1 2011
Externally published	Yes

All Science Journal Classification (ASJC) codes

Atomic and Molecular Physics, and Optics
Engineering (miscellaneous)
Electrical and Electronic Engineering

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10.1364/AO.50.001425

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title = "Sparsity-motivated automatic target recognition",

abstract = "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.",

author = "Patel, {Vishal M.} and Nasrabadi, {Nasser M.} and Rama Chellappa",

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AB - 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.

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Sparsity-motivated automatic target recognition

Abstract

All Science Journal Classification (ASJC) codes

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