Three-dimensional phase-contrast velocity vector field mapping shows great potential for clinical applications; however measurement inaccuracies may limit the utility and robustness of the technique. While parts of the error in the measured velocity fields can be minimized by background phase estimation in static tissue and magnetic field monitoring, considerable inaccuracies remain. The present work introduces divergence-reduction processing of 3D phase-contrast flow data based on a synergistic combination of normalized convolution and divergence-free radial basis functions. It is demonstrated that this approach effectively addresses erroneous flow for image reconstructions from both fully sampled and undersampled data. Using computer simulations and in vivo data acquired in the aorta of healthy subjects and a stenotic valve patient it is shown that divergence arising from measurement imperfections can be reduced by up to 87% resulting in improved vector field representations. Based on the results obtained it is concluded that integration of the divergence-free condition into postprocessing of vector fields presents an efficient approach to addressing flow field inaccuracies.