Detection of low-altitude infrared small targets for UAVs using a density-based artificial bee colony algorithm.

The objective of this paper is to address the issue of the inadequate detection accuracy of UAVs operating at low-altitudes in conditions of weak thermal signals. To this end, an enhanced small target detection model has been proposed, which integrates density-peak clustering and an artificial bee colony optimization mechanism. In the study, multi-stage preprocessing is first performed on the infrared images. By combining Butterworth low-pass filtering, local background subtraction, and exponential high-pass filtering, weak target templates are extracted. Then, the DBABC algorithm is utilized to achieve efficient clustering and accurate identification of high-density areas. To adapt to the dynamic characteristics of the target, size change perception and environmental perturbation correction mechanisms have been introduced. The experimental results showed that the model achieved the highest detection accuracy of 91.66% and 90.38% on the FLIR and KAIST datasets, respectively, with a recall rate of over 89.6%. The model maintained a signal-to-noise ratio gain of over 23.19 dB in long-distance detection from 150 to 200 m, and the detection delay was controlled below 0.5 dB at resolutions of 3840 × 2160 and 7680 × 4320. The detection delay was controlled within 28-36 ms, which was significantly better than the advanced model. Further tests in complex weather and micro-temperature difference environments verified the robustness and wide adaptability of the proposed method under rain and fog interference, high background noise, and very low thermal contrast conditions. This study enriches the application framework of density-driven intelligent optimization strategies in the field of infrared small target detection. Moreover, it provides theoretical support and technical path for low-altitude unmanned aerial vehicles to achieve efficient and stable infrared target detection in tasks such as security patrols, disaster search and rescue, and border monitoring.