Improved subpixel edge detection for asteroid approach process images with Zernike moments
Edge detection of asteroid images is the key to achieving precise autonomous navigation during the approach process of asteroids,and it is crucial to implement precise defense measures against threats to asteroids.The existing asteroid image segmentation algorithms are inaccurate and have problems such as dense star points in the images,posing challenges to subsequent image processing.This article proposes an improved Zemike moment-based subpixel edge detection method for subpixel object segmentation in asteroid-approaching images.Firstly,a bilateral filter for image preprocessing was used.Secondly,an improved morphological gradient filter operator was used to achieve coarse pixel-level edge localization.Then,an improved Zernike moment model was used to establish 7x7 templates and calculate the optimal segmentation threshold of Zemike moments using the Otsu method to achieve subpixel accurate positioning of edge detection.Finally,the refinement algorithm is used to extract the edges of subpixel images.The simulation results show that this algorithm can achieve high-precision subpixel positioning of image edges,and research can provide a reference for future autonomous navigation and orbit determination of asteroid defense.
万方数据
维普
