Most of the norms used in the field of digital image (and volume) correlation to registertwo images (or volumes) lead to ill-posed problems. One of the frequent solutions is toenforce a restricted kinematics requiring a compromise between the richness of thesolution (i.e., the spatial resolution) and the measurement uncertainty. An alternativeroute is to use a displacement norm that permits to alleviate this compromise by the meansof a mechanical regularization used when the gray levels do not give enough information.It is then possible to compute a displacement vector for each pixel orvoxel, inducing lower residuals (in terms of experimental data) whiledecreasing the noise sensitivity. The resolution performance of these different approachesis discussed, and compared for the analysis of a tensile test on a cast iron specimenbased on a pair of tomographic images. As representative reconstructed volumes lead to alarge number of degrees of freedom, a dedicated GPU computational strategy has beendeveloped and implemented.
