River detection in high-resolution SAR data using the Frangi filter and shearlet features

River extraction plays an important role in several applications such as monitoring and navigation, and synthetic aperture radar (SAR) is one of the major sensors of remote sensing. This paper proposes an algorithm to detect a river from high-resolution SAR images mainly based on the Frangi filter and shearlet features with the help of an active contour model (ACM). The Frangi filter is firstly applied to enhance the river and then the shearlet features are computed by the shearlet transform. A rule of feature selection is then proposed to acquire the corresponding features of the river. Finally, binarization and an active contour model are implemented to extract the river. The approach is tested on SAR images and the experimental results demonstrate that the proposed method is effective.