FmCFA: a feature matching method for critical feature attention in multimodal images.

Multimodal image feature matching is a critical technique in computer vision. However, many current methods rely on extensive attention interactions, which can lead to the inclusion of irrelevant information from non-critical regions, introducing noise and consuming unnecessary computational resources. In contrast, focusing attention on the most relevant regions (information-rich areas) can significantly improve the subsequent matching phase.