Abstract
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.
| Original language | English |
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| Journal | Optics InfoBase Conference Papers |
| Publication status | Published - 2022 |
| Event | Computational Optical Sensing and Imaging, COSI 2022 - Vancouver, Canada Duration: 11 Jul 2022 → 15 Jul 2022 |