Photometric stereo reconstructs surface shape with intricate details by analyzing the light propagation process and has attracted wide range of applications such as industrial measurement. However, the presence of non-Lambertian reflections on real-world scenarios poses a significant challenge to surface normal estimation methods. Most of the existing approaches aim to achieve reasonably accurate results by filtering non-Lambertian observations through employing iterative frameworks. Based on these, this study introduces a novel surface normal estimation method that formulates the observation selection and regularization as a smooth L1 regression problem. Specifically, we sort pixels by intensities and select effective observations through a threshold strategy, the surface normal are then estimated by a smooth L1 loss function to resist non-Lambertian corrosions so that facilitate a more accurate result. The performance of the method is validated through testing on real-world datasets, with an impressive average angular error as low as 11.92°. In experiments, surface reconstruction of a turbine blade is successfully achieved, showcasing its applicability in industrial manufacturing.
White Light Interferometry (WLI) is a widely used technique for surface recovery. However, it is extremely sensitive to various external disturbances, increasing the uncertainty on measurement results. In this paper, a time-domain guided filtering-based surface recovery algorithm is proposed for WLI. The reference signal is firstly simulated according to the spectral map of illuminator employed in the system. The correlation between the actual correlogram and the simulated one is then analyzed through the generalized cubic correlation delay estimation method. The corrected correlogram is obtained as a local linear transformation of the reference one that has been shifted, where the linear coefficients are estimated using least squares analysis. The surface height is then retrieved based on mapping relationship between the phase and frequency. The capability of the proposed method on noise suppression is investigated through simulation under different levels of additive noise. In the experiment, a step height standard (VLSI,181.0nm±2.1nm) is employed, which verifies the performance of the proposed method on measurement accuracy and reliability.
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