ArticleScientific reports2016
Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- High-Fidelity Computational Microscopy via Feature-Domain Phase Retrieval.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Fourier Ptychographic Microscopy Reconstruction Method Based on Residual Local Mixture Network.Sensors (Basel, Switzerland) · 2024Article
- Optical ptychography for biomedical imaging: recent progress and future directions [Invited].Biomedical optics express · 2023Review
- Poisson Phase Retrieval in Very Low-count Regimes.IEEE transactions on computational imaging · 2022Article
- Large-scale phase retrieval.Light, science & applications · 2021Article
- Structure-dependent amplification for denoising and background correction in Fourier ptychographic microscopy.Optics express · 2020Article
- Coherent anti-Stokes Raman Fourier ptychography.Optics express · 2019Article
- Article
- Sub-Diffraction Visible Imaging Using Macroscopic Fourier Ptychography and Regularization by Denoising.Sensors (Basel, Switzerland) · 2018Article
- Fourier ptychographic microscopy with sparse representation.Scientific reports · 2017Article
- Motion-corrected Fourier ptychography.Biomedical optics express · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fourier ptychographic microscopy (FPM) is a novel computational coherent imaging technique for high space-bandwidth product imaging. Mathematically, Fourier ptychographic (FP) reconstruction can be implemented as a phase retrieval optimization process, in which we only obtain low resolution intensity images corresponding to the sub-bands of the sample's high resolution (HR) spatial spectrum, and aim to retrieve the complex HR spectrum. In real setups, the measurements always suffer from various degenerations such as Gaussian noise, Poisson noise, speckle noise and pupil location error, which would largely degrade the reconstruction. To efficiently address these degenerations, we propose a novel FP reconstruction method under a gradient descent optimization framework in this paper. The technique utilizes Poisson maximum likelihood for better signal modeling, and truncated Wirtinger gradient for effective error removal. Results on both simulated data and real data captured using our laser-illuminated FPM setup show that the proposed method outperforms other state-of-the-art algorithms. Also, we have released our source code for non-commercial use.
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Registered trials
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