Analysis of Drift Adjustment by Space Optical Camera Platform

Ren, Sanhai; Fan, Xiang Jun; Zhang, Fan; Su, Zengli

doi:10.1007/978-981-10-4837-1_31

Lecture Notes in Electrical Engineering

2017

DOI: 10.1007/978-981-10-4837-1_31

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Analysis of Drift Adjustment by Space Optical Camera Platform

Sanhai Ren¹,

Xiang Jun Fan²,

Fan Zhang³

et al.

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High-resolution dynamic inversion imaging with motion-aberrations-free using optical flow learning networks

Jin

Liu

2019

Sci Rep

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Dynamic optical imaging (e.g. time delay integration imaging) is troubled by the motion blur fundamentally arising from mismatching between photo-induced charge transfer and optical image movements. Motion aberrations from the forward dynamic imaging link impede the acquiring of high-quality images. Here, we propose a high-resolution dynamic inversion imaging method based on optical flow neural learning networks. Optical flow is reconstructed via a multilayer neural learning network. The optical flow is able to construct the motion spread function that enables computational reconstruction of captured images with a single digital filter. This works construct the complete dynamic imaging link, involving the backward and forward imaging link, and demonstrates the capability of the back-ward imaging by reducing motion aberrations.

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High-resolution dynamic inversion imaging with motion-aberrations-free using optical flow learning networks

Jin

Liu

2019

Sci Rep

View full text Add to dashboard Cite

show abstract

Precise Orbit Determination of the ZY3-03 Satellite Using the Yaw-Attitude Modeling for Drift Angle Compensation

Gong,

Liu,

Wang

et al. 2024

IEEE Sensors J.

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Analysis of Drift Adjustment by Space Optical Camera Platform

Cited by 2 publications

References 1 publication

High-resolution dynamic inversion imaging with motion-aberrations-free using optical flow learning networks

High-resolution dynamic inversion imaging with motion-aberrations-free using optical flow learning networks

Precise Orbit Determination of the ZY3-03 Satellite Using the Yaw-Attitude Modeling for Drift Angle Compensation

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