On the use of deep learning for phase recovery
Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
High-speed 3D topography measurement based on fringe projection: a review
High-speed 3D topography measurement technology is important for research and
application in virtual and augmented reality, intelligent manufacturing testing, material …
application in virtual and augmented reality, intelligent manufacturing testing, material …
Phase unwrap** using deep learning in holographic tomography
Holographic tomography (HT) is a measurement technique that generates phase images,
often containing high noise levels and irregularities. Due to the nature of phase retrieval …
often containing high noise levels and irregularities. Due to the nature of phase retrieval …
Unifying temporal phase unwrap** framework using deep learning
Temporal phase unwrap** (TPU) is significant for recovering an unambiguous phase of
discontinuous surfaces or spatially isolated objects in fringe projection profilometry …
discontinuous surfaces or spatially isolated objects in fringe projection profilometry …
Two-dimensional phase unwrap** based on U2-Net in complex noise environment
J Chen, Y Kong, D Zhang, Y Fu, S Zhuang - Optics Express, 2023 - opg.optica.org
This paper proposes applying the nested U^ 2-Net to a two-dimensional phase unwrap**
(PU). PU has been a classic well-posed problem since conventional PU methods are always …
(PU). PU has been a classic well-posed problem since conventional PU methods are always …
Large Dynamic Range and Anti-Fading Phase-Sensitive OTDR Using 2D Phase Unwrap** Via Neural Network
F Peng, X Zheng, Q Miao - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Optical fiber distributed acoustic sensing (DAS) instrument enables distributed acoustic
measurements, garnering significant attention due to its high sensitivity, superior spatial …
measurements, garnering significant attention due to its high sensitivity, superior spatial …
Deep learning as a powerful tool in digital photoelasticity: Developments, challenges, and implementation
JC Briñez-de León, H López-Osorio… - Optics and Lasers in …, 2024 - Elsevier
Stress field evaluation, through fringe order maps, has always been of great importance in
various engineering domains, providing essential insights into the mechanical response of …
various engineering domains, providing essential insights into the mechanical response of …
Unsupervised Deep Unrolling Networks for Phase Unwrap**
Phase unwrap** (PU) is a technique to reconstruct original phase images from their noisy
wrapped counterparts finding many applications in scientific imaging. Although supervised …
wrapped counterparts finding many applications in scientific imaging. Although supervised …
Deep learning phase recovery: data-driven, physics-driven, or a combination of both?
Phase recovery, calculating the phase of a light wave from its intensity measurements, is
essential for various applications, such as coherent diffraction imaging, adaptive optics, and …
essential for various applications, such as coherent diffraction imaging, adaptive optics, and …
Phase unwrap** based on channel transformer U-Net for single-shot fringe projection profilometry
G Sun, B Li, Z Li, X Wang, P Cai, C Qie - Journal of Optics, 2024 - Springer
Single-shot fringe projection profilometry (FPP) has become a more prevalently adopted
technique for retrieving the absolute phase values of the objects in intelligent manufacturing …
technique for retrieving the absolute phase values of the objects in intelligent manufacturing …