Small and dim target detection by background estimation

An effective method for small and dim moving target detection in complicated background is proposed. The proposed approach takes advantage of the Non-local means filter, and applies a novel weight calculation model based on circular mask to the original background estimation pattern. By associating similarity of grayscale distribution of the images with temporal information, the extended method estimates the complicated background precisely and extracts point target successfully. To compare existing target detection methods and the proposed one, signal-to-clutter ratio gain (SCRG) and background suppression factor (BSF) are employed for spatial performance comparison and receiver operating characteristics (ROC) is used for detection-performance comparison of the target trajectory. Experimental results demonstrate good performance of the proposed method for infrared images in complicated scene, especially for images with low signal-to-noise ratio.