One approach to reduce computational cost is through the use sparse GPs that approximate (between the gradient and function sampling), the gradient inputs may be sampled from an image in a grid format, however the addition of the function observations disrupts the required format to take advantage of Kronecker products directly, without any masking of regions. Since this paper is purely focused on the methodology of obtaining quantitative **data** from schlieren images, only some of these approaches have been considered to make the method tractable.