Fast Infrared Small Target Detection Based on Global Contrast Measure Using Dilate Operation
Ye Tang, Kun Xiong, Chunxi Wang
Abstract
Infrared small target images are not conducive to detection due to their low visibility. Although there are many algorithms have been proposed to solve this problem, existing methods inevitably struggle to strike a good balance between efficiency and performance. This letter proposes a fast infrared small target detection algorithm with a low computational time consumption, only 0.012 s, while maintaining excellent detection performance. There are only two steps in the proposed method. First, the original image is processed by dilate operation with a ring structuring element. Then, the final detection result is calculated by global contrast measure (GCM) between the original image and the processed image according to the ratio form and the difference form. The experimental results demonstrate that the proposed method consistently achieves a robust and effective performance on six real sequences. In particular, the speed of the proposed method is at least two times faster than the state-of-the-art methods.