Restoration of motion-blurred star image based on improved MIMO-UNet

Jingyi Zhang; Zhaodong Niu

doi:10.1117/12.3004112

11 October 2023 Restoration of motion-blurred star image based on improved MIMO-UNet

Jingyi Zhang, Zhaodong Niu

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128003X (2023) https://doi.org/10.1117/12.3004112
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

When observing space debris with ground-based telescopes, in some cases relative motion occurs between the star and the telescope, creating a trailing tail. Motion-blurred star images are characterized by low signal-to-noise ratio and heterogeneous motion blur. In order to improve the recovery quality of motion blurred star images, this paper constructs a motion blurred star image dataset using simulated star images. The Residual Block in the MIMO-UNet is replaced by Res FFT-Conv Block to extract the spatial domain and frequency domain information of the blurred star image. Finally, training is performed on the improved MIMO-UNet. The experimental results show that the network can improve the energy of the trailing stars and recover the shape of the trailing stars.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jingyi Zhang and Zhaodong Niu "Restoration of motion-blurred star image based on improved MIMO-UNet", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128003X (11 October 2023); https://doi.org/10.1117/12.3004112

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