Abstract
The interferometry technique is commonly used to obtain the phase information of an object in optical metrology. The obtained wrapped phase is subject to a 2π 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.
Original language | English (US) |
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Pages (from-to) | 14903-14912 |
Number of pages | 10 |
Journal | Optics Express |
Volume | 27 |
Issue number | 10 |
DOIs | |
State | Published - 2019 |
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics