A new small-target detection method in forward-looking infrared images (FLIR) is proposed. The goal is to identify target locations, with low false alarms, in thermal infrared images of a natural battlefield. Unlike previous approaches, the proposed method deals with small-target detection in low-contrast images, and it is able to determine centers of targets accurately. The method comprises three distinct stages. The first stage is called center-surround difference, whose function is to find salient regions in an input image. In the second stage, local fuzzy thresholding is applied to the region of interest that is chosen from the result of the first step. The extracted binary objects are potential targets that will be classified as valid targets or clutters. Finally, using size and affinity measurements, the potential targets are compared with target templates to discard clutters in the third stage. In the experiments, many natural infrared images are used to prove the effectiveness of the proposed method. The proposed method is compared to previously reported approaches to verify its efficiency.