Enhanced high dynamic range 3D shape measurement based on generalized phase-shifting algorithm
Minmin Wang, Guangliang Du, Canlin Zhou, Chaorui Zhang, Shuchun Si,, Hui Li, Zhenkun Lei, YanJie Li

TL;DR
This paper introduces a generalized phase-shifting algorithm that enhances high dynamic range 3D shape measurement by effectively combining regular and inverted fringe patterns, improving accuracy and extending applicability over previous methods.
Contribution
It proposes a novel generalized phase-shifting approach that unifies and extends prior high dynamic range 3D measurement techniques, addressing their limitations.
Findings
Improved measurement accuracy compared to Jiang's method.
Expanded scope to handle more saturated pixels.
Validated through simulations and experiments.
Abstract
It is a challenge for Phase Measurement Profilometry (PMP) to measure objects with a large range of reflectivity variation across the surface. Saturated or dark pixels in the deformed fringe patterns captured by the camera will lead to phase fluctuations and errors. Jiang et al. proposed a high dynamic range real-time 3D shape measurement method without changing camera exposures. Three inverted phase-shifted fringe patterns are used to complement three regular phase-shifted fringe patterns for phase retrieval when any of the regular fringe patterns are saturated. But Jiang's method still has some drawbacks: (1) The phases in saturated pixels are respectively estimated by different formulas for different cases. It is shortage of an universal formula; (2) it cannot be extended to four-step phase-shifting algorithm because inverted fringe patterns are the repetition of regular fringe…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
