Phase imaging for digital holography with deep learning

Chencen Xiong, Zhenbo Ren, Jianglei Di, Jianlin Zhao
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Abstract

Deep learning has been widely employed for digital holographic reconstruction. In this paper, we present a learning-based method for phase imaging from digital holograms without complicated and notorious operations such as phase unwrapping.
基于深度学习的数字全息相位成像
深度学习在数字全息重建中得到了广泛的应用。在本文中,我们提出了一种基于学习的方法来从数字全息图中进行相位成像,而不需要复杂和臭名昭著的操作,如相位展开。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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