提出一种SAR图像目标识别新方法.首次引入BM3D方法,用于滤除原始图像中的相干斑噪声,BM3D结合了空间域和变换域去噪的优势,滤波性能优异.在特征提取步骤,将低阶Hu矩与高阶Zernike矩组合,Hu矩描述目标的粗略信息,高阶Zernike矩描述目标的细节信息,因此组合矩能够更加全面而细致地表达目标特性.使用组合矩特征训练SVM分类器,对含噪的SAR图像进行识别实验.实验结果表明:本文方法的识别率高达98.90％,优于已有的SAR目标识别方法.
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