Spatial-temporal compressive imaging using an unfolding network

Dingaoyu Zhao, Edmund Y. Lam, Jun Ke*

*此作品的通讯作者

科研成果: 期刊稿件会议文章同行评审

摘要

We propose an unfolding network GapUNet for spatial-temporal compressive imaging. Simulation and optical experiments demonstrate the network performance using compression ratios of 128: 1 and 16: 1. The mean PSNR of the reconstructed objects is higher than 29dB.

源语言英语
期刊Optics InfoBase Conference Papers
出版状态已出版 - 2022
活动Computational Optical Sensing and Imaging, COSI 2022 - Vancouver, 加拿大
期限: 11 7月 202215 7月 2022

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