Watercraft Detection in Short-Wave Infrared Imagery Using A Tailored Wavelet Basis

被引：2

作者：

Olson, C. C. ^{[1
]}

Judd, K. P. ^{[2
]}

Chander, K. ^{[3
]}

Smith, A. J. ^{[3
]}

Conant, M. ^{[4
]}

Nichols, J. M. ^{[2
]}

机构：

[1] Sotera Def Solut, Crofton, MD 21114 USA

[2] Naval Res Lab, Washington, DC 20375 USA

[3] V Syst Inc, Satellite Beach, FL USA

[4] ONR SEAP Student, Satellite Beach, FL USA

来源：

AUTOMATIC TARGET RECOGNITION XXII | 2012年 / 8391卷

关键词：

Dictionary learning; K-SVD algorithm; Sparse representations; AUTOMATIC TARGET RECOGNITION; CORRELATOR;

D O I：

10.1117/12.919943

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

We present a technique for small watercraft detection in a littoral environment characterized by multiple targets and both land- and sea-based clutter. The detector correlates a tailored wavelet model trained from previous imagery with newly acquired scenes. An optimization routine is used to learn a wavelet signal model that improves the average probability of detection for a fixed false alarm rate on an ensemble of training images. The resulting wavelet is shown to improve detection on a previously unseen set of test images. Performance is quantified with ROC curves.

引用

页数：11

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