关键词: 语义分割, 卫星图像分割, 编码和解码, 注意力机制模块

Abstract:

In order to solve the problem of edge information loss in satellite image segmentation, a Multi-Attention Mechanism Network （MA-Net） algorithm is proposed to solve the problem of edge information loss. The framework of the algorithm adopts an end-to-end symmetric structure, which consists of two parts：encoding and decoding. In the coding part, the improved VGG16 network is used to extract the texture features of the lake, and in the decoding part, the Global average Pooling Attention fusion mechanism（GPA） is introduced to effectively fuse the texture features extracted in the coding part and obtain the high-resolution satellite image feature map. At the output of the network, attention mechanism module is added to fully extract the edge information of the lake and effectively segment the peninsula, island and small tributary of the lake. The experimental results show that the model has better segmentation accuracy than the existing semantic segmentation algorithm, and each segmentation index has been improved, and the model is verified to be universal on the public data set city scales.

Key words: semantic segmentation, satellite image segmentation, coding and decoding, attention mechanism module