在感兴趣的区域层面上进行SAR图像变化检测的方法研究

摘要

A novel approach which works at the region level is proposed based on extracting and handling region of interest（ROI）.It contains two key points.One is to obtain a proper label for extracting ROI by combining stationary wavelet transform（SWT）,fuzzy C-means（FCM） clustering algorithm with inter-scale fusion strategy.The other is to generate the final change detection map at the region level through the act of searching all connected regions and then looking at each one as a unit to handle.In virtue of both points,this method has both quantitative and qualitative performances superior over other related methods.Results tested on the real SAR datasets have also confirmed this.%提出一种基于抽取和处理感兴趣区域,在区域层面上决策生成变化检测结果的技术。该技术包含两个关键点。一个是借用平稳小波变换（stationary wavelet transform,SWT）,结合模糊C-均值（fuzzy C-means,FCM）聚类算法和尺度间融合策略获取抽取感兴趣区域的标签。另一个是依据标签搜索感兴趣区域内所有的连通区域,并把每个连通区域看做为一个数据点,以使变化检测结果在区域层面上生成。借助于这两点,本文方法结果的主观效果和客观性能都优于其他相关技术。对真实SAR图像数据集的变化检测结果证实本文方法的有效性。