2 results about "Sar image segmentation" patented technology

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.

The invention discloses a multi-mode remote sensing image semantic segmentation method and device combining an optical image and an SAR (Synthetic Aperture Radar). The method comprises the following steps: inputting an optical image and an SAR image into a multi-mode remote sensing image semantic segmentation network to obtain an image segmentation result; the processing process of the multi-mode remote sensing image semantic segmentation network comprises the following steps: inputting an optical image into an optical branch to obtain an optical image segmentation result, and inputting an SAR image into an SAR branch to obtain an SAR image segmentation result; the features corresponding to the optical images output by the optical branches and the features corresponding to the SAR images output by the SAR branches are fused to obtain optical-SAR fusion features, and the optical-SAR fusion features are input into the fusion feature branches to obtain a fusion semantic segmentation result. According to the method, the ability of the model to express semantic and detail features by using optical-SAR cross-modal features is significantly improved, and a more efficient solution is provided for improvement of prediction accuracy of a remote sensing image semantic segmentation method.