An Optical Flow-Based Approach For The Interpolation Of Minimally Divergent Velocimetry Data

Three-dimensional (3D) biomedical image sets often have in-plane resolutions that are exceedingly higher than the out-of-plane spacing between images. Image interpolation can be used to reduce the effective out-of-plane spacing. Optical flow and/or other registration-based interpolators have proven useful in interpolating this type of data in the past. When acquired images are comprised of signals that describe the flow velocity of incompressible fluids, additional information is available to guide the interpolation process. In this paper, we present an optical-flow based framework for image interpolation that also minimizes resultant divergence in the interpolated data.