Infrared small-target detection based on multi-directional multi-scale high-boost response

Abstract

As of late, infrared (IR) small-target detection technology is broadly utilized in low-altitude monitoring frameworks, target-tracking frameworks, precise guidance frameworks and forest fire prevention frameworks. In this paper, we propose an infrared small-target detection strategy based on multi-directional multi-scale high-boost response (MDMSHB). First, an eight-direction filtering template is proposed, which can consider the directional information of the image and significantly suppress heterogeneous background such as cloud, linear interference and interface like ocean–sky background. Then, a map based on multi-directional multi-scale high-boost response (MDMSHB map) is calculated. Finally, a straightforward threshold segmentation technique is utilized to get the detection result. The simulation results comparing this method with the four state-of-the-art strategies in six sequences demonstrate that the proposed strategy can adequately suppress heterogeneous background and arbitrary noise. The approach can improve detection rate and reduce false alert rate as well.