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Real-time dynamic star image registration is essential for star pattern recognition and target tracking. To ensure real-time registration within limited computing resources, a semi-analytical Fourier-Mellin method is introduced for estimating registration parameters. The proposed method uses the position information and connected-domain areas of extracted star points to calculate the Fourier spectra, in contrast to the conventional pixel-level Fourier transform. Consequently, the method demonstrates exceptional computational efficiency and resilience to amplitude fluctuations in deep-space backgrounds. Additionally, an innovative one-dimensional cross-correlation function is proposed for determining registration parameters, significantly reducing the number of search operations and computational complexity compared to traditional two-dimensional functions. Furthermore, a global coarse and local fine positioning strategy is implemented to enhance the framework's efficiency while maintaining registration accuracy. Numerical experiments validate that the proposed scheme constitutes a robust and real-time process for star image registration, making it a practical solution for on-orbit platforms with constrained computing and storage capabilities.
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Chen et al. (2025) studied this question.
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