Infrared small target image segmentation based on hybrid Gaussian background modeling

Abstract

Aiming at the problems of small infrared targets occupying few pixels and complex background interference, hybrid Gaussian background modeling is adopted. Since the background image between adjacent frames does not change much, the target change is displaced. The features of each pixel in the image are represented by K weighted Gaussian models, and when a new frame of image is obtained, the hybrid Gaussian model is updated, and each pixel in the current image is matched with the mixed Gaussian model, and if successful, the point is judged to be the background point, otherwise it is the foresight. Experiments show that using the weighting of multiple Gaussian model distributions to represent the background can better adapt to the complex environment.