Enhanced Infrared Target Detection: Integrating Anti-Interference and Multi-Scale Perception

Infrared target detection using unmanned aerial vehicles (UAVs) presents a frontier in intelligent infrared recognition with diverse applications. However, challenges such as complex noise interference and drastic target scale variations hinder practical implementation. This study introduces an infrared target detection algorithm that integrates anti-interference and multi-scale perception mechanisms. The algorithm features a vision Transformer(ViT)-based anti-interference feature encoder and a multi-scale feature encoder with deformable attention. Experimental results on the HIT-UAV and VT-MOT datasets demonstrate a 4.5 and 5.3 percentage point improvement in small-target detection accuracy, respectively, highlighting its robust anti-interference capabilities and high practical applicability.