The study focused on improving image segmentation for aviation images. Researchers developed a new statistical iterative method to enhance thresholding, which helps in separating objects from the background in images. By analyzing global and local thresholding characteristics, they found that the statistical iterative method significantly improved noise resistance and segmentation quality compared to traditional methods. This approach effectively handles lighting variations and background complexities in aviation images, leading to more accurate and reliable segmentation results.