Infrared small target detection in a wide field imaging system

Small target detection in wide-area surveillance is a challenging task. Current imaging staring sensors in practical systems are characterized by large pixel counts and wide field of view (WFOV). Therefore, it is not suitable to detect targets simply via a single algorithm in different background types. We solve this problem by local windowing approach and take different background suppression and target enhancement methods for different surveillance scenarios. Monte Carlo simulations are provided and the experimental results demonstrate that we can effectively detect dim small targets with a very low false alarm rate and an acceptable detection rate in the proposed detection architecture.