Inverting color transforms
We consider experimental methods for creating regular grids for applications such as color management where the grids must be estimated from non-grid samples. To estimate the regular grid, we propose applying a generalization of linear interpolation, called linear interpolation with maximum entropy (LIME). Evaluating different estimation methods for this problem is difficult and does not correspond to the standard statistical learning paradigm of using iid training and test sets in order to compare algorithms. In this paper we consider the experimental issues and propose considering the end goal of the regular grid in evaluating an estimated grid's value. Preliminary experimental results compare LIME, traditional linear interpolation, linear regression and ridge regression.