Research on UAV Image Semantic Segmentation Algorithm for Vegetation Protection in Offshore Areas
Coastal zones have a profound impact on human life and economic development.UAV has been widely used in marine ecological protection.However,existing segmentation models still have some problems in UAV coastal zone vegetation segmentation tasks.Therefore,this paper designs a feature extraction network combined with CNN and Transformer,and then designs a MEAFormer branch.Meanwhile,a class-guided weighting module(CGW)is designed to learn the robust feature representation of different appearances.On the other hand,there are similar vegetation category segmentation errors and unclear underwater vegetation boundary segmentation caused by coastal zone scenes.Therefore,this paper constructs a fusion branch including mixed Convolution attention module(MCA)and dual attention fusion mod-ule(DAFM)to integrate and learn features of different levels.Meanwhile,SAM branch is introduced.The Mask obtained by the MEAFormer branch guides SAM to do fine segmentation.The MIou achieved 79.8%on Cityscapes and 72.4%on OUC-UAV-SEG,respectively,the effec-tiveness of the segmentation strategy proposed in this paper was verified.
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