Infrared small target detection based on non-convex triple tensor factorisation

In the present infrared target detection system, simultaneously achieving both the target detection performance, as well as, computing efficiency is considered as a big task. To, address the above said issue, a non-convex triple tensor factorisation is incorporated into the existing infrared patch tensor model in the proposed work. In the proposed model (triple tensor factorisation-infrared patch tensor), local prior information using linear structure tensor and corner strength is incorporated so that the strong clutters in the background can be easily suppressed and the target can be detected correctly. Finally, the method proposed, was solved by alternating direction method of the multiplier. Large number of experiments were conducted and the results presented in the experiments suggest that the method proposed has shown good performance for background suppression, as well as, for the target detection in the clutter environment, when compared with the other baseline methods.