A Least Trimmed Square Method for Clutter Removal in Infrared Small Target Detection

摘要

In this paper, a new procedure based on least trimmed square for clutter background estimation is proposed. Least trimmed square method identifies multiple outliers in the image, such as noise and target region. Then the clutter background is estimated without these outliers. The performance of this method is compared with the algorithms based on least mean square method, the results show that our method gets higher signal clutter ratio (SCR) gain in target region than other methods which use LMS filter.