Fourier ptychographic microscopy (FPM) is a recently proposed computationalimaging technique with both high resolution and wide field-of-view. In currentFP experimental setup, the dark-field images with high-angle illuminations areeasily submerged by stray light and background noise due to the lowsignal-to-noise ratio, thus significantly degrading the reconstruction qualityand also imposing a major restriction on the synthetic numerical aperture (NA)of the FP approach. To this end, an overall and systematic data preprocessingscheme for noise removal from FP's raw dataset is provided, which involvessampling analysis as well as underexposed/overexposed treatments, then followedby the elimination of unknown stray light and suppression of inevitablebackground noise, especially Gaussian noise and CCD dark current in ourexperiments. The reported non-parametric scheme facilitates great enhancementsof the FP's performance, which has been demonstrated experimentally that thebenefits of noise removal by these methods far outweigh its defects ofconcomitant signal loss. In addition, it could be flexibly cooperated with theexisting state-of-the-art algorithms, producing a stronger robustness of the FPapproach in various applications.
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