期刊
OPTICS EXPRESS
卷 26, 期 15, 页码 19388-19405出版社
Optica Publishing Group
DOI: 10.1364/OE.26.019388
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资金
- National Natural Science Foundation of China (NSFC) [61675113, 61527808, 81571837]
- Science and Technology Research Program of Shenzhen City [JCYJ20160428182247170, JCYJ20170412170255060, JCYJ20160324163759208, JCYJ20170412171856582]
Traditional digital holographic imaging algorithms need multiple iterations to obtain focused reconstructed image, which is time-consuming. In terms of phase retrieval, there is also the problem of phase compensation in addition to focusing task. Here, a new method is proposed for fast digital focus, where we use U-type convolutional neural network (U-net) to recover the original phase of microscopic samples. Generated data sets are used to simulate different degrees of defocused image, and verify that the U-net can restore the original phase to a great extent and realize phase compensation at the same time. We apply this method in the construction of real-time off-axis digital holographic microscope and obtain great breakthroughs in imaging speed. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
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