Small infrared target detection using minimum variation direction interpolation

Abstract

Small infrared target localization and tracking are of great importance in early-warning systems. In order to accurately localize the target, a high-performance target detection algorithm is required. In this paper, a new detection algorithm is proposed, which effectively enhances the target area and eliminates noise and background clutter. The algorithm is inspired by the minimum variation directions interpolation. The detection performance of the method is investigated comprehensively in different situations. Also, to exclude the effect of thresholding on the detector's performance, a measure based on constant false alarm rate (CFAR) is employed. Experiments on multiple real-world infrared sequences demonstrate the effectiveness of the proposed method. © 2021 Elsevier Inc.