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Related Concept Videos

Time and frequency -Domain Interpretation of Phase-lead Control01:24

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Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
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Related Experiment Video

Updated: Oct 17, 2025

Measurement of X-ray Beam Coherence along Multiple Directions Using 2-D Checkerboard Phase Grating
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Phase Error Analysis and Correction for Crossed-Grating Phase-Shifting Profilometry.

Fuqian Li1, Wenjing Chen1

  • 1Department of Opto-Electronics, Sichuan University, Chengdu 610065, China.

Sensors (Basel, Switzerland)
|October 13, 2021
PubMed
Summary

Crossed-grating phase-shifting profilometry (CGPSP) for 3D shape measurement is sensitive to non-linearity. This study introduces gamma correction to effectively reduce errors, enabling faster and more reliable measurements.

Keywords:
crossed grating projectioninverse pattern projectionnonlinearity phase error analysisphase error correctionphase shifting profilometry

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Area of Science:

  • Optical Metrology
  • 3D Shape Measurement

Background:

  • Crossed-grating phase-shifting profilometry (CGPSP) is valuable for 3D shape measurement.
  • CGPSP's sensitivity to digital fringe projection non-linearity is a significant challenge.

Purpose of the Study:

  • To analyze phase errors caused by non-linearity in CGPSP.
  • To develop and compare methods for mitigating non-linearity errors.

Main Methods:

  • Established a mathematical model to analyze non-linearity-induced phase errors.
  • Proposed a double five-step algorithm for passive non-linearity suppression.
  • Introduced a precoding gamma correction method for active non-linearity attenuation.

Main Results:

  • The active gamma correction method is more effective and requires fewer fringe patterns than passive methods.
  • Demonstrated reduced non-linearity error using the proposed gamma correction.
  • Achieved faster and more reliable inverse pattern projection with CGPSP and gamma correction.

Conclusions:

  • Non-linearity significantly impacts CGPSP accuracy.
  • Active gamma correction offers a superior solution for mitigating non-linearity in CGPSP.
  • The developed methods enhance the reliability and efficiency of 3D shape measurement using CGPSP.