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Wavelet-Assisted Adaptive EKF Phase Shift Estimation Approach for Motion-Induced Error Compensation.

Xin Lai1, Qiushuo Yu1, Zhenyi Chen2

  • 1School of Mechanical and Electrical Engineering, Southwest Petroleum University, Chengdu 610500, China.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a wavelet-assisted adaptive extended Kalman filter (WAEKF) to address motion errors in phase-shifting profilometry (PSP). The new method accurately estimates phase shifts, significantly reducing 3D reconstruction errors in dynamic scenes.

Keywords:
extended Kalman filtermotion-induced compensationphase estimationstate-space modelwavelet transform

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Area of Science:

  • Optics and Photonics
  • Computer Vision
  • Metrology

Background:

  • Phase-shifting profilometry (PSP) is sensitive to motion-induced phase-step variations in dynamic environments.
  • These variations lead to significant errors like ripples, distortions, and reduced accuracy in 3D reconstructions.
  • Existing PSP methods often assume fixed phase shifts, which is problematic for dynamic scenes.

Purpose of the Study:

  • To develop a robust method for estimating pixel-wise phase shifts in dynamic scenes.
  • To mitigate motion-induced phase errors in phase-shifting profilometry.
  • To improve the accuracy and reliability of 3D reconstruction from fringe patterns.

Main Methods:

  • A wavelet-assisted adaptive extended Kalman filter (WAEKF) is proposed to estimate varied pixel-wise phase shifts.
  • A wavelet-based strategy is used to extract initial spatial carrier frequency from fringe patterns for EKF.
  • A state-space model incorporating quadrature phase components and carrier frequency is established, utilizing a forward-backward filter.

Main Results:

  • The proposed WAEKF method successfully acquires accurate initial carrier frequency and phase shift maps.
  • Experimental results demonstrate a significant reduction in 3D reconstruction error.
  • The method effectively compensates for motion-induced phase errors in dynamic scenes.

Conclusions:

  • The wavelet-assisted adaptive extended Kalman filter provides an effective solution for motion artifacts in PSP.
  • The method enhances the accuracy of 3D reconstruction in dynamic environments.
  • This approach is adaptable and can be extended to N-step PSP systems.