Abstract In this paper we discuss image registration techniques with a focus on volume preserving constraints. These constraints can reduce the non-uniqueness of the registration problem significantly. Our implementation is based on a constrained optimization formulation. To solve the problem we use a variant of the Sequential Quadratic Programming method. Moreover, we present results on synthetic as well as on real-life data.