Date Published: March 4, 2022
A new paper in Optics Express Vol. 30, Issue 2 features the work of Chengyu Wang, Minghao Hu, Yuzuru Takashima, Timothy J. Schulz, and David J. Brady. The team uses convolutional neural networks to recover images optically down-sampled by 6.7 × using coherent aperture synthesis over a 16 camera array. Where conventional ptychography relies on scanning and oversampling, here the researchers apply decompressive neural estimation to recover full resolution image from a single snapshot, although as shown in simulation multiple snapshots can be used to improve signal-to-noise ratio (SNR). In place training on experimental measurements eliminates the need to directly calibrate the measurement system. The work also presents simulations of diverse array camera sampling strategies to explore how snapshot compressive systems might be optimized. Read the full published paper.
Comparing the reconstruction results with different aperture distributions. The full resolution images were reconstructed but only the zoomed-in details of the reconstructed images are shown for easy comparison.