u-net CNN based fourier ptychography

• URL: http://arxiv.org/abs/2003.07460v1
• Date: Mon, 16 Mar 2020 22:48:44 GMT
• Title: u-net CNN based fourier ptychography
• Authors: Yican Chen, Zhi Luo, Xia Wu, Huidong Yang, and Bo Huang
• Abstract summary: We propose a new retrieval algorithm that is based on convolutional neural networks. Experiments demonstrate that our model achieves better reconstruction results and is more robust under system aberrations.
• Score: 5.46367622374939
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Fourier ptychography is a recently explored imaging method for overcoming the diffraction limit of conventional cameras with applications in microscopy and yielding high-resolution images. In order to splice together low-resolution images taken under different illumination angles of coherent light source, an iterative phase retrieval algorithm is adopted. However, the reconstruction procedure is slow and needs a good many of overlap in the Fourier domain for the continuous recorded low-resolution images and is also worse under system aberrations such as noise or random update sequence. In this paper, we propose a new retrieval algorithm that is based on convolutional neural networks. Once well trained, our model can perform high-quality reconstruction rapidly by using the graphics processing unit. The experiments demonstrate that our model achieves better reconstruction results and is more robust under system aberrations.

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