基于分割窗的无监督多通道遥感图像变化检测

A new split window-based method for unsupervised change detection in multichannel remotely sensed images

摘要:

在遥感图像中，当变化区域的面积比例相对较大或较小时，一般的变化检测方法并不能准确地检测出变化信息。针对这一问题，本文提出一种基于分割窗的无监督多通道遥感图像变化检测方法。该方法将差异图像分割成子图像，通过求子图像的局部阈值来确定差异图像的整体阈值。实验结果表明，该方法能较好地解决变化区域相对较大或较小时一般变化检测方法无法进行准确的变化检测的问题，相对于一般变化检测的方法，检测精确度明显提高。

Abstract:

When percentage of changed area in whole scene is relatively too small or too large, general change detection methods can not detect the change information accurately. In order to solve this problem, this paper proposes a split window-based method for unsupervised change detection in multichannel remotely sensed images. This method splits difference image into a set of subimages, and determines segmentation threshold of the whole scene by combining the thresholds of subimages. Experimental results demonstrate that the proposed method can detect change information accurately even if percentage of changed area in whole scene is relatively too small or too large, and improve detection accuracy obviously comparing to general change detection methods.