DaVis is a commercially avalaible sotware package that specialises in volume corellation between data sets.

Like Digital Image Correlation (DIC) which is restricted to surface measurements, DVC calculates displacements in a complete 3D volume. Over one million displacement vectors per volume can be analyzed. StrainMaster DVC software from LaVision imports images from X-Ray CT, MRI scans, or optical tomography set-ups, and is able to quantify defects or discontinuities before they become visible in the volume image. DVC requires volume images contain a random pattern; local changes in contrast due to changes in density or voids in the case of X-ray CT scans (example in figure 1). DVC applications include biological research, metal powders, concrete structures, and composites. Dr J├╝rgen Adam (Royal Holloway University London), Dr. Klinkm├╝ller and Dr Schreurs (Bern University) have used DVC in experiments simulating geological deformation in the earth crust, and non-linear fault and fracture formation in brittle rocks. Having previously utilised DIC to monitor surface displacements of sand-box experiments, they are now successful in applying DVC to the analysis of X-Ray Tomography volume images. An excerpt of the impressive results is shown in figure 2.

Digital Image Correlation (DIC) effectively tracks the movement of the naturally occurring, or applied surface pattern during the test or experiment. This is done by analysing the displacement of the patterns within discretised subsets or facet elements of the whole image. The maximum correlation in each window corresponds to the displacement, and this gives the vector length and direction for each window. Advanced algorithms use multi-pass processing, window deformation, and the possibility of non-square subsets to maximise the sub-pixel accuracy.