Balanced Ring Top-Hat Transformation for Infrared Small-Target Detection With Guided Filter Kernel

Abstract

Detecting small targets in a complex background is always carried out by suppressing the background. The top-hat transformation is mainly utilized for background suppression in target detection. Many modified top-hat transformation methods are based on the different structures of the structural elements. However, there are two limitations. One is that the structural elements cannot sufficiently consider the contrast information between the target and surrounding area to enhance the target. Another is that structural elements should be set in advance and cannot adaptively suppress complex backgrounds. In this article, our proposed top-hat transformation is designed from two cases. First, an adaptive structural element based on a guided filter kernel is proposed for capturing the local features in infrared images for background suppression. Second, a balanced ring shape is used for two structural elements of top-hat transformation, which can utilize the contrast information between the target and background for target enhancement. More than 500 infrared target images are used in our experiment. The experimental results show that our algorithm achieves better performance in signal-to-clutter ratio gain, background suppression factor, and detection accuracy when compared with recent popular baseline methods.