Enhanced subpixel sensitivity in 3D-DIC via Spline-Based correlation map interpolation for vibration measurements

Digital Image Correlation (DIC) is a well-established technique that has recently gained interest in the field of vibration measurements. As vibration frequency increases, the displacement amplitude decreases, determining the need for extremely high subpixel measurement sensitivity. This work introduces a novel algorithm that exploits a spline-based approach to interpolate the integer-valued correlation map and enhance subpixel sensitivity. The approach allows for the calibration of the fitting procedure with respect to the local features of the speckle pattern, which is characterized by the reference image, improving the measurement's signal-to-noise ratio. The proposed procedure is compared with conventional approaches, which are based on polynomial fitting of the correlation map instead. Additionally, two different strategies are discussed to compute the integervalued correlation map, i.e. pixel domain convolution and spatial-frequency domain convolution. The algorithms' performance is assessed in terms of temporal and spatial signal-to-noise ratio using synthetic and experimental datasets.