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改进非局部均值滤波的SAR图像降噪

DOI: 10.11834/jig.20120720

Keywords: SAR图像降噪,相似集,2维主成分分析(2DPCA),非局部均值滤波(NLMF)

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Abstract:

在非局部均值滤波(NLMF)的基础上,通过预生成相似集与2DPCA(two-dimensionalprinciplecomponentanalysis)对NLMF进行改进,提出一种新的SAR(syntheticapertureradar)图像降噪方法。在NLMF算法框架下,针对SAR图像噪声的特点,首先经预处理选择邻近的子图像生成相似集,然后通过2DPCA提取子图像的主要特征,此过程减小了斑点噪声对相似性度量的影响,最后在降维后子图像的基础上进行相似性度量。通过仿真SAR图像和真实SAR图像的降噪实验,将本文方法与经典Lee滤波、Kuan滤波、Gamma-Map滤波和NLMF滤波相比较,结果表明,该方法无论在边缘保持还是一致区域的平滑上,都能取得较好的效果,是一种有效的SAR图像降噪算法。

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