Infrared dim small target detection with high reliability using saliency map fusion

Detection of dim small targets in infrared (IR) images with high reliability is very important in defence systems. In this study, a new method is introduced based on human visual system and saliency maps fusion to detect the small target in IR images with high reliability. By using the static and motion saliency maps fusion, emphasizing the obtained saliencies from one method to another and applying the information and benefits of all maps in the saliency map fusion, this method suppresses the background clutter and noise with high reliability, makes the target more prominent and finally increases the contrast among them. The experiments are carried out on some real-life data of IR images containing the moving target. The obtained results show the efficiency and robustness of the proposed method so that this method improves the target signal to the background noise and clutter and increases the contrast between them and also detects the small target in IR images with low false alarm rates and high reliability.