中文摘要：

针对多时相合成孔径雷达（Synthetic Aperture Radar,SAR）图像的变化检测,该文提出一种改进的混合变化检测方法来提高检测精度。该方法首先采用基于像素级的变化检测方法提取初始变化区域,并以此估计初始聚类中心;然后采用模糊聚类（FCM）将变化前后SAR图像分为3类,即水体区域、背景区域、过渡区域;接着采用最近距离聚类（NNC）将过渡区域像素进一步划分为水体和背景两部分,合并所有水体像素,实现洪水区域的提取。最后得到的洪水区域差异图即为最终的变化检测结果。该文采用Sentinel-1A获取的淮河与鄱阳湖水域数据进行算法验证,实验表明,该文方法的检测率较高,且总体误差较低。

英文摘要：

An improved Hybrid Change Detection（HCD）method is proposed for multi-temporal Synthetic Aperture Radar（SAR）images.Firstly,a Pixel-Based Change Detection（PBCD）method is used to extract the initial change area,and the initial cluster center is estimated based on its results.Then,Fuzzy Clustering Method（FCM）is used to get three clusters,which including water,background,and the intermediate area.The Nearest Neighbor Clustering（NNC）is adopted as the second-level clustering to divide the pixels belonging to the intermediate area into water and background respectively,afterwards merge all pixels belonging to water.Finally,the difference map of flood region in the time series images is calculated to get the final change detection result.The algorithm is validated by the Sentinel-1A data obtained from Huaihe River and Poyang Lake.The results show that our proposed method can achieve better correctness and has lower total error compared to other methods.