272 citations · 336 across the 10 of their papers we have counts for
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Deep-learning-enabled geometric constraints and phase unwrapping for single-shot absolute 3D shape measurement
Jiaming Qian, Shijie Feng, Tianyang Tao +4
Fringe projection profilometry (FPP) is one of the most popular three-dimensional (3D) shape measurement techniques, and has becoming more prevalently adopted in intelligent manufa…
On a universal solution to the transport-of-intensity equation
Jialin Zhang, Qian Chen, Jiasong Sun +2
Transport-of-intensity equation (TIE) is one of the most well-known approaches for phase retrieval and quantitative phase imaging. It directly recovers the quantitative phase distr…
Temporal phase unwrapping using deep learning
Wei Yin, Qian Chen, Shijie Feng +5
The multi-frequency temporal phase unwrapping (MF-TPU) method, as a classical phase unwrapping algorithm for fringe projection profilometry (FPP), is capable of eliminating the pha…
Microscopic 3D measurement of shiny surfaces based on a multi-frequency phase-shifting scheme
Yan Hu, Qian Chen, Yichao Liang +3
Microscopic fringe projection profilometry is a powerful 3D measurement technique with a theoretical measurement accuracy better than one micron provided that the measured targets…
Optimal illumination pattern for transport-of-intensity quantitative phase microscopy
Jiaji Li, Qian Chen, Jiasong Sun +3
The transport-of-intensity equation (TIE) is a well-established non-interferometric phase retrieval approach, which enables quantitative phase imaging (QPI) of transparent sample s…
Fringe pattern analysis using deep learning
Shijie Feng, Qian Chen, Guohua Gu +5
In many optical metrology techniques, fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns. Despite e…