Snapshot Ptychography on Array cameras

Abstract

We use convolutional neural networks to recover images optically down-sampled by $6.7\times$ using coherent aperture synthesis over a 16 camera array. Where conventional ptychography relies on scanning and oversampling, here we 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 SNR. In place training on experimental measurements eliminates the need to directly calibrate the measurement system. We also present simulations of diverse array camera sampling strategies to explore how snapshot compressive systems might be optimized.

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• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
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Cited by in corpus (1)

• Pose correction scheme for camera-scanning Fourier ptychography based on camera calibration and homography transform