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Motion-blurred star image restoration based on multi-frame superposition under high dynamic and long exposure conditions

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Abstract

Under high dynamic and long exposure conditions, the number of recognized stars on motion-blurred star images decreases, thereby degrading the attitude accuracy of star sensors. To improve the attitude accuracy, a restoration method based on multi-frame superposition, which focuses on the noise removal and quality of restored star images, is proposed for a star sensor. During each short exposure time, the corrected coordinate variation of the same star spot between adjacent star images is determined using a motion recursive model. Subsequently, the corrected star spot region is obtained, and the noise is removed. A restoration algorithm based on multi-frame superposition is proposed, taking the time consumption and quality of restored star image considered simultaneously. Simulation results indicate that the proposed restoration method based on multi-frame superposition is effective in removing noise and improving the quality of restored star images. The star recognition rate in simulation experiments verifies the advantages of the proposed method.

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Funding

National Natural Science Foundation of China (NSFC) (61503391); China Postdoctoral Science Foundation (2017M613372).

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Authors and Affiliations

  1. Xi’an Institute of High-Tech, Xi’an, 70025, China

    Yiyang He, Hongli Wang, Lei Feng & Sihai You

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  1. Yiyang He
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  2. Hongli Wang
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  3. Lei Feng
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  4. Sihai You
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Correspondence to Lei Feng.

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He, Y., Wang, H., Feng, L. et al. Motion-blurred star image restoration based on multi-frame superposition under high dynamic and long exposure conditions. J Real-Time Image Proc 18, 1477–1491 (2021). https://doi.org/10.1007/s11554-020-00965-0

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  • DOI: https://doi.org/10.1007/s11554-020-00965-0

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