Road information extraction from high resolution remote sensing images based on threshold segmentation and mathematical morphology

Extracting road information rapidly and efficiently from high resolution images is one of the research hotspots and difficulties in remote sensing. This paper studied road extraction from high resolution remote sensing images based on threshold segmentation and mathematical morphology. Information like road seed points and orientations didn´t need to be given manually in this algorithm, which to some extent improved automation of road extraction. The extraction process can be expressed as follows: Firstly, remote sensing images were segmented into binary images containing road information through threshold way. Then mathematical morphology operations are used to process binary image, extracting road regions according to road morphological characteristics. Finally, road centerline and contour were extracted by exploiting relevant mathematical morphology operations, which was proved by numerous experiments.