Method of infrared small target detection based on Contourlet transform and Facet model

It is a problem to detect small moving target in infrared images, especially under the circumstances of complex background and noise. Now aiming at this problem, a novel method based on cycle spinning Contourlet transform and the multi-orientation gradient character of Facet model was proposed. Firstly, through cycle spinning Contourlet transform, the infrared image was decomposed so that the noise was removed and the signal-to-noise ratio and smoothness were increased. Then, a median filter based on the multi-orientation gradient character of facet model was designed to filter the reconstructed image, so the complex background and noise were restrained effectively. After that, the algorithm of 2-level maximum between-cluster variance was used to segment the filtered image. Finally, further detection of the small target was made according to the relationship of position and velocity in images. The results prove that the method concerned in this paper can restrain the complex background with strong clutter to good effect and can test small target efficiently.