The invention discloses a method for carrying out
change detection on
remote sensing images based on treelet fusion and
level set segmentation, and mainly solves the problem that much pseudo-change information exists in the existing
change detection methods. The method is implemented through the following steps: inputting two time-phase
remote sensing images, then respectively carrying out
mean shift filtering on each image so as to obtain two time-phase filtered images; respectively carrying out two-dimensional stationary
wavelet decomposition on the two time-phase filtered images three times under different level numbers; carrying out subtraction on
wavelet coefficient matrixes of corresponding directional son-bands of the filtered images with the same
decomposition level number; carrying out enhancement and two-dimensional
wavelet inverse transformation reconstruction on wavelet coefficient difference matrixes in
horizontal and vertical directions by using a
sobel operator; and fusing the reconstruction images with different
decomposition level numbers so as to obtain a final difference map by using a treelet
algorithm, then carrying out
level set segmentation on the differencemap so as to obtain a
change detection result. By using the method disclosed by the invention, the accuracy of the change detection result can be improved effectively, and the edge feature of a change area can be maintained better, therefore, the method can be applied to the fields of
natural disaster analysis, land resource monitoring, and the like.