Improved Method for Small Infrared Target Detection

In order to further improve the accuracy and real-time performance of small infrared target detection,a new improved method is proposed.First,aiming at the characters of the infrared image,the improved Top-Hat filter is used to restrain background for the purpose of increasing the target detection probability.Second,the bound set is constructed to limit the gray level histogram to region of interest for reducing the interference of background and noise.Then target detection is achieved by image segmentation using improved OTSU algorithm.Furthermore,the fast recurring algorithm is applied to proposed algorithm for accelerating the running speed of the segmentation algorithm.Different types of infrared images are selected to compare the results of purposed algorithm and the other two algorithms in references.Experiment results show that proposed algorithm has better performance than the other two markedly.Object segmentation is more accurate and running speed is accelerated by more than 60%.Finally,the bound histogram can be constructed aiming at concrete problem,based on gained prior knowledge,so it has better generality.