Road information extraction from IKONOS imagery based on clustering analysis and mathematical morphology

In this paper, we present an approach based on clustering analysis and mathematical morphology to extract road information from IKONOS imagery. This road information extraction approach includes several key modules: Texture analysis based on the multi-band image to obtain two new features of "MLen/MWid" to improve the road clustering analysis; In order to optimize the primal binary imagery of road object area resulting from clustering Process, a texture analysis defined on binary imagery-"BATS" is presented, which ulteriorly expel the non-road pixels from the road area binary imagery; Furthermore, we carry out the process to extract road centerline network from the binary imagery of road object area based on mathematical morphology, through the process, several other methods, such as connectivity analysis, raster to vector transform, etc, are integrated.