High-resolution remote sensing image road extraction method based on double attention mechanism and semantic constraint

• Main Authors: NING BO, LIU AILIN, LI XUNGEN, MA QI, LI ZIXUAN, PAN MIAN, ZHANG ZHAN, LYU SHUAISHUAI, MEN FEIFEI, ZHOU SHANGCHAO
• Format: Patent
• Language: Chinese; English
• Published: 02.10.2020
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention discloses a high-resolution remote sensing image road extraction method based on a double attention mechanism and a semantic constraint angle. The method comprises the following steps: S1, operating remote sensing road images in a Massachusetts data set to perform data amplification of the data set, and performing data preprocessing operation of semantic constraint angle calculationon label images of the remote sensing road images in the data set; S2, extracting a feature map of the remote sensing road image by using a convolutional neural network, and adding a position attention mechanism and a channel attention mechanism into the convolutional neural network to calculate feature weights of different channels and positions, so that the network model can better obtain semantic information of different positions and different channels; S3, designing a main loss function and an auxiliary loss function to optimize network parameters; and S4, testing the test sample set by using the trained model, a