Infrared small target detection based on an image-patch tensor model

Infrared small target detection under complex background has been applied to many fields and is still a challenging problem. In this paper, a small target detection method base on an image-patch tensor (IPT) model is proposed. Firstly, considering the structural relationship between pixels, the original single-frame image is constructed as a new image-patch tensor. Secondly, based on the correlation of the background image patch and the sparsity of the target image patch, the small target detection problem can be transformed into an optimization problem of separating the low-rank part and the sparse part of the tensor. Finally, after simple post filtering, the target is separated adaptively. Experimental results show that the proposed method can detect the small target precisely and can keep a higher signal-to-clutter ratio (SCR). What’s more, compared with other methods, the proposed method shows better detection performance.