Abstract:

In this paper, an automatic change detection method based on fusion of spectral and geometrical features for multi-temporal high-resolution remote sensing image is proposed. Firstly, as to the characteristic of complicated classes in urban area, spectral and geometrical difference images are developed using multi-temporal images. Secondly, with difference image as input, the membership images of changed and unchanged classes are acquired using
fuzzy classification method. Thirdly, a fusion model based on fuzzy logic theory is used to combine all kinds of membership images in order to reduce the fuzziness and to distinguish the changed and unchanged classes of special areas efficiently. Finally, change detection result is obtained using threshold segmentation algorithm and accuracy evaluation is given. Multi-temporal high-resolution images of urban area are taken as experimental data, and the experimental results prove that the change detection result fusing spectral and geometrical features has higher detection precision and lower undetected ratio compared with those from spectral or geometrical difference image methods.

Key words: fusing spectral, remote sensing changes, detection method, high-resolution image, fuzzy set