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作者:

Sun, Yan (Sun, Yan.) | Wang, Dayong (Wang, Dayong.) (学者:王大勇) | Wang, Yunxin (Wang, Yunxin.) (学者:王云新) | Zhao, Jie (Zhao, Jie.) | Rong, Lu (Rong, Lu.) (学者:戎路)

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摘要:

In the present of microscopic imaging technology, both the large imaging field of view (FOV), and high-resolution are required. The Fourier ptychographic microscopy (FPM) does not need to move the sample and can keep the original FOV unchanged. It can expand the frequency bandwidth and reconstruct high-resolution intensity and phase images by using the angle diversity and synthetic aperture. It has a very important application prospect in the field of biomedical detection. However, the LED, used as the illumination source in the FPM, is an extended light source, and the light emitting unit with a certain size will cause the image blurring. Therefore, a reconstruction algorithm based on Lucy-Richardson (L-R) deconvolution is proposed in this paper. The experimental results show that the proposed algorithm can solve the problem of image blurring in FPM imaging and improve the imaging quality. © 2020 SPIE.

关键词:

Light Light sources Imaging techniques Image enhancement Optical instruments Deconvolution Fourier transforms Light emission Synthetic apertures

作者机构:

  • [ 1 ] [Sun, Yan]College of Applied Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Wang, Dayong]College of Applied Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Wang, Dayong]Beijing Engineering Research Center, Precision Measurement Technology and Instrument, Beijing; 100124, China
  • [ 4 ] [Wang, Yunxin]College of Applied Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zhao, Jie]College of Applied Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Rong, Lu]College of Applied Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Rong, Lu]Beijing Engineering Research Center, Precision Measurement Technology and Instrument, Beijing; 100124, China

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ISSN: 0277-786X

年份: 2020

卷: 11434

语种: 英文

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