Road Network Extraction from Remote Sensing Image Based on a Marked Point Process

A method based on the Bayesian theory is presented to extract road networks in remote sensing images. A model based on a marked point process is designed to exploit as fully as possible the properties of the network,and the optimization is done via simulated annealing using a Reversible Jump Markov Chain Monte Carlo algorithm.A new preprocessing method is proposed to extract the location and orientation information.A birth-and-death proposal kernel based on preprocessing is proposed to reduce the searching space.A move proposal kernel based on connection is proposed to accelerate the convergence of the algorithm.The experimental results show that this method can extract road networks from different kinds of remote sensing images fast and efficiently.