匹配子空间检测器在SAR图像树木目标识别中的应用

A. Sharma, R. Moses
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引用次数: 8

摘要

我们研究了在低频合成孔径图像中使用基于子空间的探测器来区分车辆和树木。我们将树散射建模为结构化的各向同性干扰响应,将主导车辆散射建模为二面体响应。我们形成树和目标响应的线性子空间,并应用Scharf和Friedlander(1994)开发的基于子空间的检测方法。对合成树和目标模型的分析表明了该方法的可行性。在实测图像上的初步结果提供了较低的性能,这表明需要改进数据校准和改进低频树木散射模型。
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Matched subspace detectors for discrimination of targets from trees in SAR imagery
We investigate the use of subspace-based detectors for discriminating vehicles from trees in low frequency synthetic aperture imagery. We model tree scattering as structured isotropic interference responses and model dominant vehicle scattering as dihedral responses. We form linear subspaces of tree and target responses, and apply subspace-based detection methods developed by Scharf and Friedlander (1994). Analysis on synthetic tree and target models show the viability of this approach. Preliminary results on measured imagery provide lower performance, suggesting the need for improved data calibration and improved scattering models of trees at low frequencies.
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