一种有效的高分辨率SAR目标特征提取与识别方法
An Effective Method for Targets Feature Extraction and Recognition of High Resolution SAR Images
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摘要: 提出了一种有效的高分辨率SAR目标特征提取与识别方法,根据SAR图像目标对多尺度Gabor滤波器组的不同响应,充分利用多尺度信息及尺度间的相依性提取新的多尺度特征,该特征综合考虑了SAR图像目标的宏观和微观固有的尺度特性,从而更能反映目标的本质特征;并利用Fisher核映射使得非线性变换比线性变换更能刻画实际中的复杂模式。实验给出了MSTAR数据库中三类目标特征的空间聚类及分类情况,结果表明了该多尺度特征的有效性。Abstract: An effective method for high resolution synthetic aperture radar(SAR) images feature extraction and target recognition is presented.According to the different response characters of targets to multi-scales Gabor filters,multi-scale information and the pertinence between multi-scales are adopted to extract new multi-scale features.This new feature combines target's macroscopical and microcosmical characteristic together,that makes it easy to obtain more essential features of SAR image.Nonlinear transform that
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