Paper Info
Title
Experimental robustness of Fourier ptychography phase retrieval algorithms
Abstract
Fourier ptychography is a new computational microscopy technique that provides gigapixel-scale intensity and phase images with both wide field-of-view and high resolution. By capturing a stack of lowresolution images under different illumination angles, an inverse algorithm can be used to computationally reconstruct the high-resolution complex field. Here, we compare and classify multiple proposed inverse algorithms in terms of experimental robustness. We find that the main sources of error are noise, aberrations and mis-calibration (i.e. model mis-match). Using simulations and experiments, we demonstrate that the choice of cost function plays a critical role, with amplitude-based cost functions performing better than intensity-based ones. The reason for this is that Fourier ptychography datasets consist of images from both brightfield and darkfield illumination, representing a large range of measured intensities. Both noise (e.g. Poisson noise) and model mis-match errors are shown to scale with intensity. Hence, algorithms that use an appropriate cost function will be more tolerant to both noise and model mis-match. Given these insights, we propose a global Newton's method algorithm which is robust and accurate. Finally, we discuss the impact of procedures for algorithmic correction of aberrations and mis-calibration. (C) 2015 Optical Society of America
Year
DOI
Venue
2015
10.1364/OE.23.033214
OPTICS EXPRESS
Field
DocType
Volume
Inverse,Phase retrieval,Ptychography,Computational photography,Optics,Algorithm,Robustness (computer science),Fourier transform,Shot noise,Amplitude,Physics
Journal
23
Issue
ISSN
Citations 
26
1094-4087
14
PageRank 
References 
Authors
1.49
5
8
Name
Order
Citations
PageRank
lihao yeh1141.49
jonathan dong2152.86
Jingshan Zhong3142.16
Lei Tian4152.88
Michael Chen5151.86
Gongguo Tang650536.29
Mahdi Soltanolkotabi740925.97
laura waller8396.72