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Proceedings Paper

A positional misalignment correction method for Fourier ptychographic microscopy based on simulated annealing
Author(s): Jiasong Sun; Yuzhen Zhang; Qian Chen; Chao Zuo
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Paper Abstract

Fourier ptychographic microscopy (FPM) is a newly developed super-resolution technique, which employs angularly varying illuminations and a phase retrieval algorithm to surpass the diffraction limit of a low numerical aperture (NA) objective lens. In current FPM imaging platforms, accurate knowledge of LED matrix’s position is critical to achieve good recovery quality. Furthermore, considering such a wide field-of-view (FOV) in FPM, different regions in the FOV have different sensitivity of LED positional misalignment. In this work, we introduce an iterative method to correct position errors based on the simulated annealing (SA) algorithm. To improve the efficiency of this correcting process, large number of iterations for several images with low illumination NAs are firstly implemented to estimate the initial values of the global positional misalignment model through non-linear regression. Simulation and experimental results are presented to evaluate the performance of the proposed method and it is demonstrated that this method can both improve the quality of the recovered object image and relax the LED elements’ position accuracy requirement while aligning the FPM imaging platforms.

Paper Details

Date Published: 10 February 2017
PDF: 5 pages
Proc. SPIE 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016), 102501I (10 February 2017); doi: 10.1117/12.2266662
Show Author Affiliations
Jiasong Sun, Nanjing Univ. of Science and Technology (China)
Yuzhen Zhang, Nanjing Univ. of Science and Technology (China)
Qian Chen, Nanjing Univ. of Science and Technology (China)
Chao Zuo, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10250:
International Conference on Optical and Photonics Engineering (icOPEN 2016)
Anand Krishna Asundi; Xiyan Huang; Yi Xie, Editor(s)

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