Abstract
The bridge identification method in the high-resolution remote sensing image is realized by using the characteristics of the bridge. Now, due to the continuous leap forward in sensing technology, the data volume of remote sensing images has increased substantially, and the resolution of remote sensing images has also been continuously improved. People are paying more and more attention to the automatic recognition and positioning of bridges in remote sensing images. Automatic bridge recognition technology can automatically extract bridge signs from the complex background of earth observation images through high-speed real-time information processing based on specific regions and various input function template databases and detect, intercept, identify, and track targets. By using the characteristics of typical targets or image edges, grayscale, texture structure meaning, and regional shape, satellite remote sensing images have the advantage of being able to provide surface information at a high speed. However, in special cases such as low resolution (medium and low), the acquisition and measurement of GIS information cannot play a good role. In order to provide a reliable guarantee for mapping and map updates, it is necessary to develop high-resolution satellite remote sensing images. Use remote sensing images with high spatial resolution as the data source, and use a rule-based object-oriented method to correctly extract bridge targets from high-resolution images. First, through multi-scale scoring experiments, combined with the characteristics of the bridge, select the best segmentation ratio. Second, the rule set is established using the water index and threshold function method, and the vector files of the water area and the bridge are gradually obtained. Finally, the bridge target can be obtained normally through binarization, mathematical shape processing, overlay analysis, and other methods.
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