Detection of infrared dim small target based on image patch contrast

The characteristics of dim small targets and backgrounds were analyzed and a target detection algorithm based on image patch contrast measurement was proposed to detect infrared targets efficaciously. The Image Patch Maximum Contrast Measurement (IPMCM) at a large scale was used to obtain a saliency map and the region of interest was segmented by an adaptive threshold. Then, the image patch least-contrast measurement maps at the multiscale were computed and the maximum pooling operation was operated. Finally, the target position was detected by the adaptive threshold accurately. The detection algorithm for small infrared targets was presented and its efficacy was analyzed theoretically. The verification and contrast experiments were conducted. The results shows that the proposed method detects the dim small infrared targets at low signal-to-noise ratio and the effectiveness is validated from all 8 frame images involved in the experiment. As compared with the local probability analysis, median filtering, and Top-Hat method, the proposed method in the target detection performance contrast test shows the highest detection rate and the lowest false alarm rate.