Small infrared target detection based on the complex filter bank

Small infrared target detection is one of the key techniques in infrared searching and tracking applications. A novel small target detection method based on the complex filter bank is proposed in this paper. Firstly, a training sample dataset is built and the complex filter bank is utilized to extract the feature representation of each pixel. Then, the support vector machine is used to detect the small target. Finally, a simple adaptive segmentation method is adopted to segment the result image. To evaluate the performance of the proposed method, background clutter suppression and small target detection probability experiments are conducted over real infrared small targets in two image sequences. The experiment results show that the proposed method can not only suppress background clutter effectively, but also detect targets accurately with low false alarm rate.