中文摘要：

针对SAR图像的分割问题,对K均值聚类算法进行研究.分析动态K均值聚类算法,用聚类样本数的正比函数对该聚类适应度函数进行平均,改进适应度函数的计算.毫米波SAR图像分割实验结果表明,对于城区建筑及路、桥场景的分割,改进后的动态K均值聚类算法和自适应动态K均值聚类算法的分割质量与改进前相同,但是分割时间有一定的减少,改进适应度函数后分割效率得到了提高.

英文摘要：

We present our study on SAR image segmentation based on K-means clustering. We analyze dynamical K-means clustering algorithms and improve the adaptation degree function computation method which divides the raw adaptation degree function by a direct ratio function of the sample number in clustering. Millimeter SAR image segmentation results verify that, for urban area, road, and bridge scenes segmentation, dynamical K-means clustering algorithm and adaptive dynamical K-means clustering algorithm with the improved adaptation degree function computation method have the same segmentation quality while the segmentation efficiency is higher than before.