SAR图像的检测和分类方法

The Detection and Classifying Technology Research of the SAR Image

从理论上分析了图像灰度共生矩阵和灰度共生矩阵的多个统计量.提出了一种基于灰度共生矩阵的C-均值聚类算法,用于对合成孔径雷达(SAR)图像的分类.通过真实的SAR图像,在实验中分析了各统计量的性能.分析表明,熵、方差、对比度、差平均的性能较好.采用这几个统计量作为特征量进行分类,得到了较好的分类结果,很好地保持了类间距,同时使类内方差较小.

Several statistics of the image gray-level co-matrix and gray-level co-matrix were first theoretically analyzed. Then a novel C-mean clustering algorithm, which is based on the gray-level co-matrix and can be used for synthetic aperture radar （SAR） image classification, was proposed. The characteristics of different statistics were obtained from experiments. The analysis shows that the entropy,variance, the contrast and mean error will perform better. It is shown that when the statistics, which will maximize the between-class scatter and minimize the within-class scatter, is adopted for classification, a much higher performance is achieved.