Analysis and comparison of Fourier Ptychographic phase retrieval algorithms
Li-Hao Yeh
EECS Department, University of California, Berkeley
Technical Report No. UCB/EECS-2016-86
May 13, 2016
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-86.pdf
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 low-resolution 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.
Advisors: Laura Waller
BibTeX citation:
@mastersthesis{Yeh:EECS-2016-86, Author= {Yeh, Li-Hao}, Title= {Analysis and comparison of Fourier Ptychographic phase retrieval algorithms}, School= {EECS Department, University of California, Berkeley}, Year= {2016}, Month= {May}, Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-86.html}, Number= {UCB/EECS-2016-86}, 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 low-resolution 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.}, }
EndNote citation:
%0 Thesis %A Yeh, Li-Hao %T Analysis and comparison of Fourier Ptychographic phase retrieval algorithms %I EECS Department, University of California, Berkeley %D 2016 %8 May 13 %@ UCB/EECS-2016-86 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-86.html %F Yeh:EECS-2016-86