A centre-scale sorting local contrast method for infrared small target detection

This paper proposes a new method for detecting small infrared targets, which addresses the issue of low detection probability (DP) and high false alarm probability (FAP) caused by false alarm sources such as high bright background edge or independent noise. The method employs a three-layer window for local contrast calculation to obtain a more accurate reference value of the background, which can enhance real targets and suppress complex backgrounds. It also solves the problems of multi-scale target detection and independent noise removal by using rank order filtering of fixed center window. Furthermore, targets are enhanced using the gray scale distributions of their edges contrast calculation, thereby improving the DP and reducing the FAP. Experimental validation on several infrared sequences and images confirms the effectiveness and robustness of the proposed method, which outperforms five existing algorithms in terms of DP and FAP.