Radon transform enables precise alignment of space debris images
Sub-Pixel Affine Registration of Space Debris Images via the Radon Point Spread Function
Computer Vision and Pattern RecognitionGraphics
Summary
Images of space debris taken from moving platforms often shift and rotate slightly, making it hard to analyze them together. The authors created a new way to measure these shifts and rotations very accurately by transforming the images using a mathematical tool called the Radon transform. Their method needs very little data, no guessing, and works well even when images are noisy. Tests with simulated and real images show their technique is better than what’s usually needed for combining multiple images.
What this means in practice
- •For satellite imaging teams: Improve alignment of low-quality sequential images of space debris for more accurate tracking and analysis.
- •For ground-based telescope operators: Precisely register images of point-like celestial targets despite jitter and attitude changes without heavy computation.
Authors
Shenshen Luan, Miaomiao Tian, Shuai Jiang, Yan Yang, Shuguo Xie, Zezhou Sun
Abstract
Inter-frame affine misalignment caused by platform jitter and attitude adjustments poses a fundamental challenge for multi-frame analysis of point targets in optical surveillance. Conventional registration methods rely on spatial intensity correlations or distinctive image features, both of which are largely absent in low-signal-to-noise-ratio point target imagery. We introduce the Radon Point Spread Function (RPSF) to characterize point targets in the Radon-transformed domain, and derive a closed-form framework that jointly estimates inter-frame translation and rotation from as few as four scalar RPSF samples per frame pair. The method requires no iterative optimization, feature extraction or interpolation, which is suitable for resource-constrained onboard processing. Simulation results confirm sub-pixel translation accuracy and a mean rotation error of 0.2556° at 1° Radon angular resolution. Validation on five real space debris datasets including both ground-based and in-orbit observations yields a mean calibration error below 0.5 pixels, substantially exceeding the precision required for reliable multi-frame processing.