Remote sensing image segmentation is a specific task of remote sensing image interpretation. A good remote sensing image segmentation algorithm can provide guidance for environmental protection, agricultural production, and urban construction. This paper proposes a new type of UNet image segmentation algorithm based on channel self attention mechanism and residual connection called . In my experiment, the new network model improved mIOU by 2.48% compared to traditional UNet on the FoodNet dataset. The image segmentation algorithm proposed in this article enhances the internal connections between different items in the image, thus achieving better segmentation results for remote sensing images with occlusion.
翻译:遥感图像分割是遥感图像解译的一项特定任务。良好的遥感图像分割算法可以为环境保护、农业生产和城市建设提供指导。本文提出了一种基于通道 self attention 机制和残差连接的新型 UNet 图像分割算法称为 Deep Attention UNet。在我的实验中,与传统的 UNet 相比,新的网络模型在 FoodNet 数据集上将 mIOU 提高了 2.48%。本文提出的图像分割算法增强了图像中不同项之间的内部连接,从而实现了对具有遮挡的遥感图像更好的分割结果。