Unsupervised change detection using a novel fuzzy c-means clustering simultaneously incorporating local and global information

This paper presents a novel fuzzy c-means (FCM) clustering simultaneously incorporating local and global information (FLGICM) method to unsupervised change detection (CD) from remotely sensed images. A new factor including three local, global and edge parameters is added into the conventional FCM to enhance the insensitivity to noise and preserve detailed… CONTINUE READING