Neural network model assisted Fourier ptychography with Zernike aberration recovery and total variation constraint.

Journal: Journal of biomedical optics
Published Date: Mar 1, 2021

Abstract

SIGNIFICANCE: Fourier ptychography (FP) is a computational imaging approach that achieves high-resolution reconstruction. Inspired by neural networks, many deep-learning-based methods are proposed to solve FP problems. However, the performance of FP still suffers from optical aberration, which needs to be considered.

Authors

  • Yongbing Zhang
    Tsinghua Univ. Shenzhen International Graduate School, China.
  • Yangzhe Liu
    Tsinghua Univ. Shenzhen International Graduate School, China.
  • Shaowei Jiang
    Univ. of Connecticut, United States.
  • Krishna Dixit
    Univ. of Connecticut, United States.
  • Pengming Song
    Univ. of Connecticut, United States.
  • Xinfeng Zhang
  • Xiangyang Ji
    Department of Automation, Tsinghua University, Main building, Haidian District, Beijing 100084, People's Republic of China.
  • Xiu Li
    Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China.

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