Digital volume correlation (DVC) is a 3D pattern recognition technique used for correlation analysis of volumetric image data, typically acquired with x-ray microtomography. The technique is used to determine the three-dimensional structural deformation of the investigated object. The calculations are based upon two sets of volumetric data collected from the object before and after deformation. Just as for the two-dimensional algorithm we divide the initial data sets into smaller regimes, called subvolumes or correlation windows. Each subvolume contains three-dimensional randomly distributed features - analogue with the speckle patterns in the 2D case. Within these subvolumes we calculate the three-dimensional displacement by finding the position and orientation of the same pattern of features in the deformed volume. Then by repeating the procedure for the whole volume we achieve the full three-dimensional deformation field. Finally, from the obtained displacements it is possible to determine the 3D strains in the material due to the structural deformation.
A thorough description of DVC can be found in this PhD-thesis.