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Fourier ptychography (FP) is a powerful light-based synthetic aperture imaging technique that allows one to reconstruct a high-resolution, wide field-of-view image by computationally integrating a diverse collection of low-resolution, far-field measurements. Typically, FP measurement diversity is introduced by changing the illumination angle or the position of the camera; either approach results in sampling different portions of the sample's spatial frequency content, but both approaches introduce substantial cost and complexity to the acquisition process. In this work, we introduce inverse synthetic aperture Fourier ptychography, a novel approach to FP that foregoes changing the illumination angle or camera position and instead generates measurement diversity through sample tilt. Critically, we also introduce a novel learning-based method for estimating the sample's orientation from dual plane intensity measurements, thereby enabling synthetic aperture imaging without explicit knowledge of the tilt angle. We experimentally validate our method in simulation and on a tabletop optical system.
Chan et al. (Wed,) studied this question.
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