Mixed integer ink selection for spectral reproduction

Abstract

We introduce a novel ink selection method for spectral printing. The ink selection algorithm takes a spectral image and a set of inks as input, and selects a subset of those inks that results in optimal spectral reproduction. We put forward an optimization formulation that searches a huge combinatorial space based on mixed integer programming. We show that solving this optimization in the conventional reflectance space is intractable. The main insight of this work is to solve our problem in the spectral absorbance space with a linearized formulation. The proposed ink selection copes with large-size problems for which previous methods are hopeless. We demonstrate the effectiveness of our method in a concrete setting by lifelike reproduction of handmade paintings. For a successful spectral reproduction of high-resolution paintings, we explore their spectral absorbance estimation, efficient coreset representation, and accurate data-driven reproduction.