MGAF-net: Gaussian saliency features guided infrared small target detection network

Robust infrared dim small target detection under sparse features is a difficult problem in the field of small target detection. Therefore, in order to solve this problem, this paper proposes an infrared dim small target detection network based on multi-scale Gaussian significance and attention feature fusion (MGAF)-net. In MGAF-net, MGAF module is proposed to extract multi-scale Gaussian saliency features of small targets. At the same time, in order to better fuse the multi-scale Gaussian saliency features of the target, the attention mechanism is introduced in the MGAF module to enrich the feature expression of the target. The experimental results show that the proposed detection method has higher detection accuracy and higher detection speed than the existing advanced infrared dim small target detection methods. This paper proposes an infrared dim small target detection network based on multi-scale Gaussian significance and attention feature fusion (MGAF)-net. MGAF-net solves the problem of small target detection under sparse features.image