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Adaptive denoising method based on iterative process for Fourier ptychographic microscopy
Author(s): Yao Fan; Jiasong Sun; Qian Chen; Chao Zuo
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Paper Abstract

Fourier ptychographic microscopy (FPM) is a wide-field and high-resolution (HR) imaging technique, reconstructing HR spectrum from a series of low-resolution (LR) images captured at different illumination angles. In FPM, the quality of captured images is a critical factor that affects the final reconstruction HR result, so an effective denoising method is an indispensable process step. Here we propose an adaptive denoising method for FPM, which takes advantage of the data redundancy of FPM to separate signal from noise without any pre-knowledge about the noise statistics. Different from the traditional denoising method by reducing a fixed threshold, the proposed adaptive denoising method can more effectively eliminate noise and preserve more effective signals. This paper explains adaptive denoising principle and process steps, and finally demonstrates that this method not only improve the accuracy and robustness of FPM, but also relax the imaging performance requirement for implementing high-quality FPM reconstruction.

Paper Details

Date Published: 24 July 2018
PDF: 5 pages
Proc. SPIE 10827, Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018), 108273O (24 July 2018); doi: 10.1117/12.2500843
Show Author Affiliations
Yao Fan, Nanjing Univ. of Science and Technology (China)
Jiasong Sun, 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. 10827:
Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018)
Yingjie Yu; Chao Zuo; Kemao Qian, Editor(s)

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