Infrared small target detection based on kernel anisotropic diffusion

In order to reduce the effect that caused by background edge of the infrared image, a robust small target detection algorithm is proposed. Firstly, a kernel anisotropic diffusion model is used to predict the background. Then, targets are extracted from the residual map between the original image and its predicted background image. In order to improve the algorithms adaptive ability, a robust diffusion parameter is proposed which can automatically adjust diffusion parameter based on the fluctuation of the images background. The experimental results demonstrate that the proposed algorithm has better performance in the suppression of background and its edge, the reservation of targets size, the reduction of false-alarm probability, and the robustness compared with the state-of-the-art algorithms under various typical complex backgrounds.