A Road Extraction Method Using Dual-Temporal High-Resolution SAR Images

This paper introduces a method of road extraction using dual-temporal high-resolution synthetic aperture radar (SAR) images. Firstly, multiplicative Duda operators are applied to detect line features. Then, coherence and backscattering coefficient are combined to distinguish road from river and shadow and the coefficient of variation is used to remove heterogeneous areas. Next, road is segmented via path opening and thresholding. At last, a novel thinning and gap connection approach is proposed to gain the thinned and more complete road map. The experiments were test on TerraSAR-X images and results showed that the proposed method improved considerably the results of road extraction compared with approach using single-temporal SAR image.