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Acquiring road junction information is helpful for improving the quality of road network extraction. This article presents a new road network extraction method with three stages. First, road junction candidates are extracted by our previously proposed valley-finding algorithm. Second, numerous particle filters running in parallel track road centrelines starting from all of the detected junction candidates. Finally, the road centrelines are approximated by fitting the tracked centrepoints. The main contribution of this article lies in two aspects. First, road centrepoint tracking routes are launched simultaneously by considering the detected road junctions as starting points, which helps overcome the interference of various obstacles. Second, parallel tracking is implemented by a graphics processing unit (GPU) running accelerated particle filters, which significantly improves the execution time of the road network extraction task. The experimental results show that our proposed method not only handles various obstacles that occur on the roads capably, but also, on average, is 10.5 times as fast as previous methods. We compared the proposed method with two other existing methods in the literature using two different synthetic aperture radar (SAR) images to validate the superior performance of our proposed method.
Cheng et al. (Wed,) studied this question.