This literature review investigates the integration of machine learning (ML) into optical metrology, unveiling enhancements in both efficiency and effectiveness of measurement processes. With a focus on phase demodulation, unwrapping, and phase-to-height conversion, the review highlights how ML algorithms have transformed traditional optical metrology techniques, offering improved speed, accuracy, and data processing capabilities. Efficiency improvements are underscored by advancements in data generation, intelligent sampling, and processing strategies, where ML algorithms have accelerated the metrological evaluations. Effectiveness is enhanced in measurement precision, with ML providing robust solutions to complex pattern recognition and noise reduction challenges. Additionally, the role of parallel computing using graphics processing units and field programmable gate arrays is emphasised, showcasing their importance in supporting the computationally intensive ML algorithms for real-time processing. This review culminates in identifying future research directions, emphasising the potential of advanced ML models and broader applications within optical metrology. Through this investigation, the review articulates a future where optical metrology, empowered by ML, achieves improved levels of operational efficiency and effectiveness.

A field-portable, single-shot and very simple method is presented for measuring the full complex degree of coherence (CDC) of a quasi-monochromatic Schell-model field using the Fresnel diffraction from a phase discontinuity. To validate the proposed technique, the CDC of the light emitted from an incoherent source with variable size is investigated. The results are in excellent agreement with theoretical predictions of the Van Cittert–Zernike theorem. This technique is also applicable to characterize the coherence properties of sources in other spectral regions, e.g., x-rays.

Interference microscopy, particularly coherence scanning interferometry (CSI),¹ is a popular optical technique for high-precision surface topography measurement.^2,3 The broad range of CSI applications, from high-precision measurements of semiconductor devices to quality control in industrial manufacturing, has motivated the development of physics-based models to predict interference signals and analyze measurement results.^{4 – 7} The development of these models addresses the practical need for a better understanding of the instrument characteristics and performance specifications, optimization of instrument configurations for good practice, and uncertainty estimation using virtual instruments.

<!-- *** Custom HTML *** --> A common-path spatial phase shifting digital speckle pattern shearing interferometry setup is introduced for simultaneous measurement of in-plane and out-plane strain components under dynamic loading using two laser beams with different wavelengths that symmetrically illuminate the test object and a single detector. The simplicity, stability, and efficiency of the arrangement are provided by using a glass plate as a shearing device, which is capable of tuning the sensitivity continuously. The phase is recovered from a single frame by the Fourier method. In this setup, the spatial carrier frequencies can be adjusted independent of the amount of the lateral shear. Ultimately, the desired field of view can easily be achieved by simple imaging optics. To validate the feasibility and the flexibility of our technique, the proposed setup is used to evaluate the in-plane and out-plane strain maps of an aluminum plate, which is deformed under dynamic stress in its plane. The temporal phase stability of the proposed system is also investigated.