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Dual-wavelength interferogram decoupling method for three-frame generalized dual-wavelength phase-shifting interferometry based on deep learning
- Source :
- Journal of the Optical Society of America. A, Optics, image science, and vision. 38(3)
- Publication Year :
- 2021
-
Abstract
- In dual-wavelength interferometry, the key issue is how to efficiently retrieve the phases at each wavelength using the minimum number of wavelength-multiplexed interferograms. To address this problem, a new dual-wavelength interferogram decoupling method with the help of deep learning is proposed in this study. This method requires only three randomly phase-shifted dual-wavelength interferograms. With a well-trained deep neural network, one can obtain three interferograms with arbitrary phase shifts at each wavelength. Using these interferograms, the wrapped phases of a single wavelength can be extracted, respectively, via an iterative phase retrieval algorithm, and then the phases at different synthetic beat wavelengths can be calculated. The feasibility and applicability of the proposed method are demonstrated by simulation experiments of the spherical cap and red blood cell, respectively. This method will provide a solution for the problem of phase retrieval in multiwavelength interferometry.
- Subjects :
- Light
Phase (waves)
Physics::Optics
Spherical cap
01 natural sciences
010309 optics
Optics
Deep Learning
0103 physical sciences
Physics
Artificial neural network
business.industry
Deep learning
Astrophysics::Instrumentation and Methods for Astrophysics
Signal Processing, Computer-Assisted
Decoupling (cosmology)
Models, Theoretical
Atomic and Molecular Physics, and Optics
Electronic, Optical and Magnetic Materials
Interferometry
Wavelength
Computer Vision and Pattern Recognition
Artificial intelligence
business
Phase retrieval
Subjects
Details
- ISSN :
- 15208532
- Volume :
- 38
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Journal of the Optical Society of America. A, Optics, image science, and vision
- Accession number :
- edsair.doi.dedup.....9d3ab15c35d0c3d671d23125bebb6756