The Infrared Patch-Image(IPI)small target detection method has a wide range of applications in the fields of data chain,early warning,guidance,etc.For example,data chain can be used to accurately transmit IPI of small targets to the radar.In order to further improve the effects of infrared small target detection under complex background conditions,this paper proposes an IPI small target detection algorithm combining reweighting with local a priori.Firstly,the weighted Schatten p norm is used to constrain the background patch image.Secondly,the prior information of local contrast and the weighted l1 norm are introduced to suppress sparse non-target points,which further enhances the sparsity of the target image and further improves the performance of the algorithm model.The simulation results show that the proposed algorithm has better results than the existing classic algorithms in background clutter suppressing and accurate target detecting.
关键词
目标检测/红外小目标/稀疏低秩分解/红外图像块
Key words
target detection/infrared small target/sparse low-rank decomposition/infrared patch image
维普
万方数据