نبذة مختصرة : International audience ; Digital Image Correlation typically involves deforming a pixelated image in order to compare its grey levels with those of another image. To achieve sub-pixel accuracy, grey-level interpolation is required. However, this interpolation is non-physical and introduces biases that become particularly detrimental under finite strains. In this work, we propose an alternative photometric approach that entirely avoids interpolation, grounded in a rigorous formulation of the direct image formation problem. The inverse problem is then posed as the joint estimation of a super-resolved digital twin-representing the scene and sensor characteristics-and the displacement fields. Both are estimated by minimising a single cost function that compares all available real images to their synthetic counterparts generated through a physically based rendering model. This minimisation is performed using an efficient alternating minimisation scheme. Several two-dimensional test cases are analysed, demonstrating that the proposed method is effectively unbiased and exhibits significantly lower uncertainties than state-of-the-art DIC techniques.
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