  We present a novel algorithm explicitly tailored to estimate motion from time
series of 3D images of concrete. Such volumetric images are usually acquired by
Computed Tomography and can contain for example in situ tests, or more complex
procedures like self-healing. Our algorithm is specifically designed to tackle
the challenge of large scale in situ investigations of concrete. That means it
cannot only cope with big images, but also with discontinuous displacement
fields that often occur in in situ tests of concrete. We show the superior
performance of our algorithm, especially regarding plausibility and time
efficient processing. Core of the algorithm is a novel multiscale
representation based on morphological wavelets. We use two examples for
validation: A classical in situ test on refractory concrete and and a three
point bending test on normal concrete. We show that for both applications
structural changes like crack initiation can be already found at low scales --
a central achievement of our algorithm.
