为了实现对SAR（合成孔径雷达）图像的无监督自动分割,提高分割精度和计算效率,提出了一种基于非下采样Contourlet变换（NSCT）和模糊c均值（FCM）聚类的SAR图像分割方法.该方法首先采用一种基于NSCT的去噪算法对SAR图像进行去噪预处理,以保护细节纹理信息;然后采用保边缘灰度特征提取方法和灰度共生矩阵来提取SAR图像的灰度特征和纹理特征;最后将改进的快速确定聚类类别数的方法与FCM聚类算法相结合,对SAR图像进行自动分割.实验结果表明,文中所提方法是一种精度和效率较高的SAR图像无监督自动分割方法.

In order to realize the unsupervised and automatic segmentation of SAR（Synthetic Aperture Radar） ima-ges and improve the accuracy and computational efficiency of segmentation,a segmentation method of SAR images based on NSCT（Non-subsampled Contourlet Transform） and FCM（Fuzzy c-Means） clustering is proposed.In this method,first,a denoising method based on NSCT is used to preprocess SAR images,which may protect the details of texture information.Then,the gray and texture features of SAR images are extracted by an edge-preserving extraction method of gray feature and gray-level co-occurrence matrix.Finally,the improved method of fast determining the clustering number is combined with the FCM clustering algorithm to realize the automatic segmentation of SAR images.Experimental results show that the proposed method is precise and effective in the unsupervised and automatic segmentation of SAR images.