Journal
OPTICS EXPRESS
Volume 27, Issue 10, Pages 14903-14912Publisher
Optica Publishing Group
DOI: 10.1364/OE.27.014903
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Funding
- China Scholarship Council (CSC) [201704910730]
- National Science Foundation (NSF) [1455630]
- Div Of Biological Infrastructure
- Direct For Biological Sciences [1455630] Funding Source: National Science Foundation
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The interferometry technique is corn commonly used to obtain the phase information of an object in optical metrology. The obtained wrapped phase is subject to a 27 pi ambiguity. To remove the ambiguity and obtain the correct phase, phase unwrapping is essential. Conventional phase unwrapping approaches are time-consuming and noise sensitive. To address those issues, we propose a new approach, where we transfer the task of phase unwrapping into a multi-class classification problem and introduce an efficient segmentation network to identify classes. Moreover, a noise-to-noise denoised network is integrated to preprocess noisy wrapped phase. We have demonstrated the proposed method with simulated data and in a real interferometric system. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
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