Multi-stage morphological operators for small infrared target detection

Abstract

Infrared small target detection is a challenging task. Despite the recent advances in the development of small infrared target detection algorithms, having a robust target detection algorithm with high probability of detection rate remains unaddressed. To this end, in this paper, a morphological top-hat transform is presented. The proposed method benefits from intrinsic high probability detection rate of classical top-hat transform, while the false alarm rate remains below the acceptable threshold. Also, the sensitivity to noise analysis demonstrates that the proposed method is robust against various noise intensities. The proposed method is tested on some real infrared images. The experiments show that the proposed method outperforms state-of-the-arts in both quantitative and qualitative manners.