Watercraft detection in short-wave infrared imagery using a tailored wavelet basis

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 xed 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 quantied with ROC curves.

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