基于双分支注意力增强Mamba模型的遥感图像字幕生成方法OA

Remote sensing image captioning(RSIC)is a task that combines computer vision and natural language processing,aiming to convert remote sensing images into natural language descriptions.In this paper,an image captioning method based on dual-branch attention and Mamba is proposed.In the dual-branch attention Mamba network,a bidirectional scanning Mamba module is designed.The latest Mamba architecture is adopted to encode global image features,and a bidirectional scanning mechanism is used to enhance the model's spatial perception and understanding of the image space.In the dual-branch attention module,a lightweight attention mechanism is used to effectively focus on and optimize local image features,thereby improving the overall model performance.Tests on image captioning based on the UCM-Captions dataset and Sydney-Captions dataset show that the method proposed in this paper performs better than existing methods.