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机构地区:[1]海军航空工程学院电子信息工程系,山东烟台264001
出 处:《信号处理》2012年第12期1642-1649,共8页Journal of Signal Processing
基 金:国家自然科学基金资助(61179017;61201445);"泰山学者"建设工程专项经费资助
摘 要:针对SAR图像相干斑噪声抑制和特征保持问题,建立了多尺度自卷积(MSA)和相位一致(PC)的滤波器模型,结合MSA频域变换多尺度均值和PC高精度特征定位的特点,提出了一种频域有特征保护的SAR图像相干斑噪声抑制算法。算法判断SAR图像中不同类型区域,选择不同的滤波策略。对均匀区域采用MSA滤波;由PC测度判断特征区域,并对特征区域采用PC测度加强的MSA滤波;对分离点目标区域,采用观察值与MSA算术平均滤波。算法有效地解决了空域方法对SAR图像噪声抑制效果好而易破坏细节特征的矛盾。仿真实验和滤波性能评估指标分析显示,算法具有良好的抑制SAR图像相干斑噪声和保护特征的能力。On the basis of the speckle reduction and feature preservation of SAR image, a new algorithm based on multi- scale auto-convolution (MSA) and phase congruency (PC) is proposed for SAR image speckle reduction. The multi-scale average property of MSA and the characteristic of good feature localization of PC in Fourier transform domain are combined together. At first, different filtered regions are analyzed and judged in SAR image by tile proposed algorithm. Then, the corresponding filtering strategy is adopted. The MSA filtering method is implemented in proportional and homogeneous re- gions. The enhanced MSA filtering method by measure of phase congruency is performed in the analyzed and judged as fea- ture regions according to the measure of phase congruency. The average MSA filtering method is used in the isolated point object regions. The conflict of spatial adaptive filtering methods between speckle reduction and feature preservation is deal with in SAR image speckle noise reduction. MiniSAR image data is used for verification and the experiment results indicate that the proposed algorithm has a good performance of speckle noise reduction.
分 类 号:TP79[自动化与计算机技术—检测技术与自动化装置]
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