Spatial-Temporal Subset-based Digital Image Correlation: A General Framework
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A comprehensive and systematic framework for easily extending and implementing the spatial-temporal subset-based digital image correlation (DIC) algorithm is presented. The framework decouples the three main factors (shape function, correlation criterion, and optimization algorithm) in DIC, and represents different algorithms in a uniform form. One can freely choose and combine the three factors to meet his own need, or freely add more parameters to extract analytic results. Subpixel translation and a simulated image series with different velocity characters are analyzed using different algorithms based on the proposed framework. And an application of mitigating air disturbance due to heat haze using spatial-temporal DIC (ST-DIC) is demonstrated, proving the applicability of the framework.
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