Decision-level fusion for road network extraction from sar and optical remote sensing images

In order to make the best use of the available data in the remote sensing database, this paper focuses on an important topic of using the complementary information of multi-source remote sensing data, that is, road network extraction based on fusion technology with synthetic aperture radar (SAR) and optical images. Starting with the line segments achieved from the road segmentation maps, a decision-level fusion method which mainly includes two stages is proposed in this paper. The first stage is fusing based on the geometric overlapping rules. In the second stage, a road network extraction approach that takes into account both the contextual information and evidence theory is presented. The experiments on TerraSAR-X and WorldView-4 images showed that our proposed method had an excellent performance in terms of the completeness and quality of the road extraction.