Abstract
Fourier ptychography (FP) is a recently proposed computational imaging technique for high space-bandwidth product imaging. In real setups such as endoscope and transmission electron microscope, the common sample motion largely degrades the FP reconstruction and limits its practicability. In this paper, we propose a novel FP reconstruction method to efficiently correct for unknown sample motion. Specifically, we adaptively update the sample's Fourier spectrum from low spatial-frequency regions towards high spatial-frequency ones, with an additional motion recovery and phase-offset compensation procedure for each sub-spectrum. Benefiting from the phase retrieval redundancy theory, the required large overlap between adjacent sub-spectra offers an accurate guide for successful motion recovery. Experimental results on both simulated data and real captured data show that the proposed method can correct for unknown sample motion with its standard deviation being up to 10% of the field-of-view scale. We have released our source code for non-commercial use, and it may find wide applications in related FP platforms such as endoscopy and transmission electron microscopy.
Highlights
Fourier ptychography (FP) is a novel computational imaging technique for high space-bandwidthproduct (SBP) imaging [1, 2]
The synthetic numerical aperture (NA) of the Fourier ptychographic microscopy (FPM) setup reported in ref. [1] is ∼0.5, and the FOV reaches ∼120 mm2, which greatly improve the throughput of existing microscope
We propose a novel Fourier ptychographic reconstruction method termed motioncorrected Fourier ptychography, which adds an additional sample-motion recovery and phase-offset compensation procedure to conventional alternating projection reconstruction, and adaptively updates the HR spatial spectrum from low spatial-frequency regions to high spatial-frequency regions
Summary
Fourier ptychography (FP) is a novel computational imaging technique for high space-bandwidthproduct (SBP) imaging [1, 2] This technique captures a set of low-resolution (LR) images, which correspond to different Fourier sub-spectra of the sample. By stitching these sub-spectra together in Fourier space using a reconstruction algorithm, a large field-of-view (FOV) and high-resolution (HR) image of the scene can be obtained. It has been successfully demonstrated in optical microscopy as Fourier ptychographic microscopy (FPM) [1], where the incident light is assumed to be a plane wave, and the LR images are captured under different incident angles from the LEDs placed at different locations. Due to its simple setup and super performance, FPM has been widely applied in 3D imaging [3, 4], fluorescence imaging [5, 6], mobile microscope [7, 8], and high-speed in vitro imaging [9, 10]
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