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中的特定任务。一种优秀的遥感图像分割算法能够为环境保护、农业生产及城市建设提供指导。本文提出了一种基于通道自注意力机制和残差连接的新型UNet图像分割算法，命名为Deep Attention Unet。实验结果表明，在FoodNet数据集上，该新网络模型相比传统UNet的mIOU提升了2.48%。本文所提出的图像分割算法增强了图像中不同要素之间的内在关联，从而在存在遮挡的遥感图像上取得了更优的分割效果。