A Real-Time Infrared Small Target Detection Based on Double Dilate Contrast Measure

The accurate and robust detection of small infrared (IR) targets in complex backgrounds is crucial for the effective operation of IR search and track systems. However, the high-intensity components in background regions could easily be confused with the real targets among local contrast features, which makes it an inevitable and challenging problem. To efficiently alleviate this issue, a real-time IR small target detection method is proposed by using the double dilate contrast measure (DDCM). The proposed method is a robust and efficient detector that takes into account various aspects, including target property, background information, and their interrelations. First, an enhancement layer is considered to enlarge the difference between the target and the background with dilation operation as the core component. Second, based on considering the relationship between the local maximum and regional mean, a suppression layer is introduced to further eliminate the clutter and noise from the high-intensity regions, and the dilate operation is also used as the core component. Finally, the DDCM map is obtained by fusing the enhancement and suppression layers, after which an adaptive segmentation operation is adopted to extract the small targets. Extensive experimental results on nine sequences demonstrate that DDCM outperforms other existing methods in terms of detection rate and false alarm rate while also exhibiting high efficiency.