39 research outputs found
Content adaptive sparse illumination for Fourier ptychography
Fourier Ptychography (FP) is a recently proposed technique for large field of
view and high resolution imaging. Specifically, FP captures a set of low
resolution images under angularly varying illuminations and stitches them
together in Fourier domain. One of FP's main disadvantages is its long
capturing process due to the requisite large number of incident illumination
angles. In this letter, utilizing the sparsity of natural images in Fourier
domain, we propose a highly efficient method termed as AFP, which applies
content adaptive sparse illumination for Fourier ptychography by capturing the
most informative parts of the scene's spatial spectrum. We validate the
effectiveness and efficiency of the reported framework with both simulations
and real experiments. Results show that the proposed AFP could shorten the
acquisition time of conventional FP by around 30%-60%
Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient
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 error removal. Results on both simulated data and real data captured using
our laser 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
Motion-corrected Fourier ptychography
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