The application provides a
water body boundary identification method and device based on boundary
perception collaborative optimization, belongs to the field of
artificial intelligence remote sensing SAR image segmentation, and comprises the following steps: a
deep learning model is constructed, a real-time double-
branch semantic segmentation framework is adopted to meet the timeliness requirement of
water body boundary identification; an auxiliary boundary prediction
branch is introduced to highlight high-frequency
semantic information, a
boundary detection is taken as an optimization target, and a boundary
perception loss is introduced to predict complex
water body boundaries; a pixel attention module, a context fast aggregation module and a boundary attention guiding module are proposed to mine spatial detail information, context information and boundary information of a target image respectively, control effective learning of context
semantic information, guarantee reliability and timeliness of extracted information, guide effective fusion of various information at a boundary area, jointly optimize original double-
branch and auxiliary branches, and realize accurate identification of water body boundaries. The application can improve identification precision.