【摘要】 合成孔径雷达(SAR)图像的相干斑噪声降低了影像分割和分类的效果,会导致影像判识困难。结合Con-tourlet系数的结构特点和SAR图像相干斑乘性噪声模型,提出了一种新的基于Contourlet变换的降斑算法。该算法利用信号与噪声在Contourlet域尺度间相关性的不同,通过空间选择滤波对系数进行分类,采用混合分布模型,实现了SAR图像的降斑处理。实验结果表明,该算法不仅能有效地抑制相干斑,而且还能有效地保护图像的细节特征。更多还原

【Abstract】 Speckle in synthetic aperture radar(SAR) image complicates the image interpretation by reducing the effectiveness of image segmentation and classification.Combining the characteristics of the Contourlet coefficients and the multiplicative model of the speckle on SAR image,a novel speckle reduction algorithm is proposed.The algorithm utilizes the differences of the interscale correlation between signal and noise in Contourlet domain to classify the Contourlet coefficients via SSNF(spatial selective noise filtration),and then the speckle reduction to SAR image is implemented by means of mixture-distribution model.Experiments show that the proposed algorithm outperforms other methods in achieving the best balance between speckle suppression and image detail preservation.更多还原