Space-based infrared aerial target detection method via interframe registration and spatial local contrast

Infrared aerial target detection on a space-based platform is of great importance in the field of aerospace. How-ever, the intensities of clutter may be much stronger than those of aerial targets in space-based infrared images, which causes issues in accurate aerial target detection. Existing detection methods cannot adapt well to such a situation, and often receive results with missed detections and false alarms since they are prone to enhance clutter rather than the target. To tackle such limitations, we propose a two-stage Interframe Registration and Spatial Local Contrast (IFR-SLC) based method for space-based infrared aerial target detection. In the first stage, the interframe registration model is constructed to suppress strong clutter and highlight the target. In the second stage, the spatial local contrast model is introduced to further suppress the residual background and enhance the target, which eventually generates the saliency map with only the aerial target remaining. Target extraction is conducted by setting an adaptive threshold. Five space-based sequences with different backgrounds were se-lected for evaluation, and experimental results indicated better performances of IFR-SLC compared with those of space-based or state-of-the-art detection methods.