Phase-shifting interferometry based on principal component analysis.

Area of Science:

• Optics and Photonics
• Image Processing
• Computational Science

Background:

• Phase-shifting interferometry is crucial for optical metrology.
• Existing methods often require controlled backgrounds, specific modulation, or phase shifts.
• Computational demands limit scalability for large datasets.

Purpose of the Study:

• To introduce a novel, computationally efficient, and versatile phase-shifting algorithm.
• To overcome limitations of traditional phase-shifting techniques regarding background, modulation, and phase shift constraints.
• To enable high-throughput analysis of large-scale interferometric data.

Main Methods:

• Developed an asynchronous phase-shifting technique utilizing principal component analysis (PCA).
• PCA is employed to extract two quadrature signals from interferometric data.
• The method imposes no constraints on background intensity, fringe modulation, or phase step values.

Main Results:

• The PCA-based method demonstrates high speed and minimal computational requirements.
• Successfully applied to both simulated and experimental interferogram datasets.
• Achieved satisfactory results, validating the method's effectiveness and robustness.

Conclusions:

• The asynchronous PCA phase-shifting method offers a significant advancement in interferometric data processing.
• Its low computational load and flexibility make it suitable for large image and dataset analysis.
• This technique provides a robust solution for accurate phase retrieval in diverse optical metrology applications.