3,151 research outputs found
System calibration method for Fourier ptychographic microscopy
Fourier ptychographic microscopy (FPM) is a recently proposed quantitative
phase imaging technique with high resolution and wide field-of-view (FOV). In
current FPM imaging platforms, systematic error sources come from the
aberrations, LED intensity fluctuation, parameter imperfections and noise,
which will severely corrupt the reconstruction results with artifacts. Although
these problems have been researched and some special methods have been proposed
respectively, there is no method to solve all of them. However, the systematic
error is a mixture of various sources in the real situation. It is difficult to
distinguish a kind of error source from another due to the similar artifacts.
To this end, we report a system calibration procedure, termed SC-FPM, based on
the simulated annealing (SA) algorithm, LED intensity correction and adaptive
step-size strategy, which involves the evaluation of an error matric at each
iteration step, followed by the re-estimation of accurate parameters. The great
performance has been achieved both in simulation and experiments. The reported
system calibration scheme improves the robustness of FPM and relaxes the
experiment conditions, which makes the FPM more pragmatic.Comment: 18 pages, 9 figure
Data preprocessing methods for robust Fourier ptychographic microscopy
Fourier ptychographic microscopy (FPM) is a recently proposed computational
imaging technique with both high resolution and wide field-of-view. In current
FP experimental setup, the dark-field images with high-angle illuminations are
easily submerged by stray light and background noise due to the low
signal-to-noise ratio, thus significantly degrading the reconstruction quality
and also imposing a major restriction on the synthetic numerical aperture (NA)
of the FP approach. To this end, an overall and systematic data preprocessing
scheme for noise removal from FP's raw dataset is provided, which involves
sampling analysis as well as underexposed/overexposed treatments, then followed
by the elimination of unknown stray light and suppression of inevitable
background noise, especially Gaussian noise and CCD dark current in our
experiments. The reported non-parametric scheme facilitates great enhancements
of the FP's performance, which has been demonstrated experimentally that the
benefits of noise removal by these methods far outweigh its defects of
concomitant signal loss. In addition, it could be flexibly cooperated with the
existing state-of-the-art algorithms, producing a stronger robustness of the FP
approach in various applications.Comment: 7 pages, 8 figure
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