SAR (Synthetic Aperture Radar) image segmentation method based on Treelets and fuzzy C-means clustering

The invention discloses an SAR (Synthetic Aperture Radar) image segmentation method based on Treelets and fuzzy C-means clustering, mainly solving the problem that target identification cannot be manually carried out on a large quantity of images in the prior art. The SAR image segmentation method comprises the steps of: 1, extracting texture features and wavelet features of an input SAR image tobe segmented; 2, forming the texture features and the wavelet features into a feature matrix; 3, carrying out Treelets conversion on the feature matrix to obtain a basis matrix; 4, multiplying the feature matrix with a scaling function of the basis matrix to obtain a structural vector; and 5, carrying out fuzzy C-means clustering on the structural vector to obtain a segmentation result of the SARimage. The invention can be used for reducing dimensions of high-dimensional data before clustering by utilizing the Treelets conversion, can effectively inhibit the noise and improve the segmentation speed of the SAR image, a