Research on Multifeature Segmentation Method of Remote Sensing Images Based on Graph Theory

Abstract

According to the characteristics of high-resolution remote sensing (RS) images, a new multifeature segmentation method of high-resolution remote sensing images combining the spectrum, shape, and texture features based on graph theory is presented in the paper. Firstly, the quadtree segmentation method is used to partition the original image. Secondly, the spectrum, shape, and texture weight components are calculated all based on the constructed graph. The matching degree between pixels and the texture is computed similarity. Finally, the ratio cut standards combination of the spectrum, shape, and texture weight components is used for the final segmentation. The experimental results show that this method can obtain more ideal results and higher segmentation accuracy applied to RS image than those traditional methods.