Infrared small target discrimination using sequential forward feature selection with AUC mettric

Abstract

Infrared search and track (IRST) is an important research topic in military applications in surveillance and precise guided missiles. The bottleneck of IRST algorithm is huge number of false alarms in real world applications due to sky cloud, sea-glints, and ground clutters. This paper presents a novel target discrimination method using forward feature selection with area under ROC curve (AUC) metric. Experimental results on real target sequences validate the feasibility of the proposed method.