Simulation of Remote Sensing Image Target Recognition Based on Convolutional Neural Network
In remote sensing images,targets are often located in complex backgrounds,including different types of vegetation,land cover and buildings.These complex backgrounds pose difficulties for target recognition.In order to accurately recognize the target in remote sensing images,this paper proposed an algorithm for recognizing targets in re-mote sensing images based on convolutional neural network.Firstly,the dark channel principle and bilateral filtering algorithm were effectively combined to enhance the remote sensing image.Then,the scale range of the target in remote sensing images was statistically analyzed.Through training and testing the convolutional neural network,we got the best scale of the target region of interest.After determining the best scale,we constructed a target recognition architec-ture based on convolutional neural network.Finally,we completed the recognition of the target in remote sensing ima-ges.Experimental analysis proves that the proposed algorithm can effectively improve the enhancement effect of remote sensing images and has good performance in recognizing the target in remote sensing images.
NETL
NSTL
万方数据
