Small target detection using center-surround difference with locally adaptive threshold

Abstract

A target detection method from low contrast forward looking infrared (FLIR) images is proposed. It is known that detecting small targets in remotely sensed image is difficult and challenging work. The goal is to identify target areas with small number of false alarms in a thermal infrared scene of battlefield. The proposed method consists of following three stages. First, center-surround difference with local adaptive threshold is proposed in order to find salient areas in an input image. Second, local thresholding is proposed to the local region of interest (ROf) based on the result of first step. The second step is needed to segment target silhouettes precisely. Third, the extracted binary target silhouettes are compared with target template using size and affinity to remove clutters. In the experiments, many natural infrared images with high variability are used to prove performance the proposed method. It is compared with a morphological method using receiver operating characteristic (ROC) curve and execution time. The result shows that our method is superior to the morphological method and it can be applied to automatic target recognition (ATR) system.