Abstract. This paper describes a new aerial images segmentation algorithm. The algorithm is based upon the knowledge of image multi-scale geometric analysis which can capture the image's intrinsic geometrical structure efficiently. The Contourlet transform is selected to represent the maximum information of the image and obtain the rotation invariant features of the image. A modified Mumford-Shah model is built to segment the aerial image by a necessary level set evolution. To avoid possible local minima in the level set evolution, we control the value of weight numbers of features in different evolution periods in this algorithm, instead of using the classical technique which evolve in a multi-scale fashion.