In order to improve the change detection accuracy of multitemporal high spatial resolution remote-sensing (HSRRS) images, a change detection method of multitemporal remote-sensing images based on saliency detection and spatial intuitionistic fuzzy C-means (SIFCM) clustering is proposed. Firstly, the cluster-based saliency cue method is used to obtain the saliency maps of two temporal remote-sensing images; then, the saliency difference is obtained by subtracting the saliency maps of two temporal remote-sensing images; finally, the SIFCM clustering algorithm is used to classify the saliency difference image to obtain the change regions and unchange regions. Two data sets of multitemporal high spatial resolution remote-sensing images are selected as the experimental data. The detection accuracy of the proposed method is 96.17% and 97.89%. The results show that the proposed method is a feasible and better performance multitemporal remote-sensing image change detection method.

中文翻译：

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基于显着性检测和空间直觉模糊C均值聚类的多时相高分辨率遥感影像变化检测

为了提高多时相遥感影像的变化检测精度，提出了一种基于显着性检测和空间直觉模糊C均值聚类的多时相遥感影像变化检测方法。首先，基于聚类的显着性提示方法用于获取两个时间遥感图像的显着性图。然后，通过减去两个时间遥感图像的显着性图获得显着性差异。最后，利用SIFCM聚类算法对显着性差异图像进行分类，得到变化区域和不变区域。选择多时相高空间分辨率遥感影像的两个数据集作为实验数据。所提方法的检测准确率分别为96.17％和97.89％。