Abstract
Road network is an important part of ground remote sensing image, and extraction of road network information plays an important role in image matching and urban planning. In recent years, high-resolution remote sensing images have attracted more and more attention of people, and object detection and recognition from high-resolution image data has become an important research topic. In this paper, the basic features of roads in high-resolution remote sensing images are briefly described, and two methods of road network extraction are analyzed and compared. It is of great significance to make better use of road features to effectively remove the interference of various noises in high-resolution images and accurately extract road information.
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