A combined approach to infrared small target detection with the alternating direction method of multipliers and an improved top-hat transformation

In infrared small target detection, the infrared patch image model (IPI) based methods produce better results than other popular approaches (such as Max-Mean, top-hat, and Human Visual System) but suffer from the long processing times and serious clutters and noises. To tackle such issues, we take a novel approach to divide the traditional target detection process into a background suppression step and a noise and clutter elimination step. The proposed method firstly adapts the alternating direction method of multipliers to preliminarily remove the background. This step does not require sliding patches thus reducing the processing time significantly. The interim results are then processed via an improved new top-hat transformation using a specifically constructed threefold structuring element, to eliminate the residual noises and clutters. The binarised segmentation is done using adaptive thresholds. The experiment results show our method can detect the infrared targets more efficiently and consistently than both the IPI and the new top-hat methods as well as some other widely used methods