Abstract
Robust and effective small-target detection in infrared (IR) imagery has significant implications for modern military operations. For the objective of achieving simultaneous solid performance in detection rate, false alarm rate (FAR), and speed, this research provides a novel method making use of local contrast measure (LCM) based on high-boost filters [novel high-boost filter improved LCM (NHBF-ILCM)]. First, a novel high-boost filter is used for target signal enhancement and background clutter suppression, followed by an ILCM used to achieve high-speed local contrast and further target resolution enhancement and clutter suppression. Then, an adaptive threshold is used to segment the target. Finally, through experiments using three sequences with different and typically complex backgrounds, the detection capabilities of the proposed method are confirmed, and these results reveal that the proposed algorithm is able to achieve the best performance and highest efficiency for real IR small-target detection applications among similar algorithms.
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