A Novel Local Contrast Method Based on Third-Order Central Moments for Infrared Small Target Detection

Danyang Xu ¹ Dongdong Pang ^2* Shimiao Gou ³ Liu Zhaoyu ³ Zhihai Zhuo ⁴

• ¹ Henan University of Science and Technology, Luoyang, Henan Province, China
• ² Beijing Institute of Technology, Beijing, Beijing Municipality, China
• ³ Zhengzhou University of Aeronautics, Zhengzhou, China
• ⁴ Beijing Information Science and Technology University, Beijing, Beijing, China

As local contrast mechanisms are extensively utilized in infrared small target detection. However, the performance of existing local contrast-based methods is often compromised in complex backgrounds.This study presents a novel local contrast method based on third-order central moments to address the above challenges. Initially, the infrared image undergoes top-hat transformation to mitigate most background clutter and highlight potential target pixels. Then, a local contrast description operator based on third-order central moments is defined to characterize the grayscale changes in different regions of the preprocessed image, enhance the target and suppress the background. Finally, the target is extracted by using an adaptive threshold segmentation operation. The experimental results in six real-life scenarios demonstrate that the proposed method occupies the best detection index compared to other similar technologies.