Sub-Pixel Affine Registration of Space Debris Images via the Radon Point Spread Function

• URL: http://arxiv.org/abs/2609.06929v1
• Date: Mon, 07 Sep 2026 01:56:13 GMT
• Title: Sub-Pixel Affine Registration of Space Debris Images via the Radon Point Spread Function
• Abstract summary: Inter-frame affine misalignment poses a fundamental challenge for multi-frame analysis of point targets in optical surveillance.<n>We introduce the Radon Point Spread Function (RPSF) to characterize point targets in the Radon-transformed domain.<n>We derive a closed-form framework that jointly estimates inter-frame translation and rotation from as few as four RPSF samples per frame pair.
• Score: 8.083475003173758
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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