Infrared small target detection method based on nonlinear local filter

In order to improve the efficiency of infrared small target detection against complex background, the image was decomposed into three regions flat region, edge region and small target region. A method of nonlinear local filter detection using the Laplaclan pyramid was presented based on each character of the three components. Firstly, Gaussian pyramids were built for the image, each level was subtracted from the original image with matching size, and the flat region was restrained by simple threshold operation. Secondly, the minimum difference between the marked pixel gray value and the mean value of the hollow annular region was used as quota to filter out the edge region. At last, each layer coefficient of the Laplacian pyramid was generated from the results of nonlinear local filtering and then a high-contrast detection image was reconstructed. The isolated noise points were removed based on the character of the neighborhood and the infrared small target was marked by simple threshold operation. Compared with other existing methods, the experimental results show that this method can effectively restrain complex background and the detection speed is fast.