Abstract:In order to improve the detection probability of dim small target in infrared image under complex background and reduce the false alarm rate,an infrared dim small target detection algorithm based on two step degree is proposed in this paper. Firstly,based on facet model,two dimensional discrete orthogonal polynomials are used to fit the local gray distribution of the original image. Then,a second order directional derivative filter is designed to filter the image and decompose it into different directional channels. Furthermore,according to the extremum theorem,the extremum image is obtained for different directional channels. The extremum image is then filtered by morphology to enhance the target energy and further suppress the target noise. Afterward,the extremum image is normalized and its histogram is counted. The histogram gray distribution is used to select the appropriate segmentation threshold. Thus after threshold segmentation,the binary image is obtained and the target position is finally determined. The experimental results show that the method can detect small and weak targets accurately in complex background with very low SNR.