Infrared Dim Target Detection Method Based on Local Feature Contrast and Energy Concentration Degree

Abstract Infrared dim target detection under complex backgrounds is of great importance in many applications. However, it is difficult for the conventional detection method to enhance dim targets and suppress clutter effectively and simultaneously, which leads to a low detection rate, poor background adaptability, and many false alarms. To address this issue, a simple method based on local feature contrast and energy concentration degree (LFC-ECD) is proposed in this paper to detect infrared dim targets under backgrounds with clutters. The LFC-ECD consists of the LFC model and ECD model; the former suppresses most background and effectively enhances the target, the latter suppresses residual clutter having similar features to the real target. Eventually, the true target is extracted from the background by adaptive threshold segmentation. The experiment is conducted on six infrared sequences that have different backgrounds and a minimum average signal-to-clutter rate (SCR) of 0.9299. The experimental results indicate that, compared with the other 7 methods, LFC-ECD not only achieves background suppression and target enhancement with higher values of the background suppression factor (BSF) and gain of SCR (GSCR) but also has a faster processing speed. In conclusion, LFC-ECD improves the effectiveness of IR dim target detection under complex background.