Target Detection of Geographic Mapping Image Based on Multi-scale Feature Fusion
In order to improve the detection accuracy of geographic mapping targets,a target detection method of geographic mapping images based on multi-scale feature fusion was designed.The edge infor-mation of the remote sensing image of geographical mapping was preliminarily extracted,and its edge density and edge distribution were calculated.Through enhancing the edge information,the remote sens-ing image was preprocessed to obtain more clear image edge information.Gradient sampling method was used to establish the descending pyramid image to provide more accurate and distinct information for sub-sequent target extraction by integrating multi-scale feature.According to the feature fusion results,the deep convolution network was used to effectively detect the geographic mapping image objects.The exper-imental results showed that the accuracy,recall and F1 score of the detection results were high after the application of this method,and the detection time was also maintained in a lower numerical range,indi-cating that the method significantly improved the detection effect for targets.
target detectiongeographic mapping imageedge informationmulti-scale featuredeep convolution networkdetection time
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