Polynomial modeling and optimization for colorimetric characterization of scanners

In this work we present different computational strategies for colorimetric characterization of scanners using multidimensional polynomials. The designed strategies allow us to determine the coefficients of an a priori fixed polynomial taking into account different color error statistics. Moreover, since there is no clear relationship between the polynomial chosen for the characterization and the intrinsic characteristics of the scanner, we show how genetic programming could be used to generate the best polynomial. Experimental results on different devices are reported to confirm the effectiveness of our methods with respect to others in the state of the art.