A Simple Color Prediction Model based on Multiple Do Gain Curves

Most of the color prediction models use single dot gain curve, few assume that dot gain changes when ink superposition happens, but still, use single dot gain curve for each ink to compensate the effective ink coverage. Considering the fact that optical dot gain is the effect of light scattering in paper, it is reasonable that light with different wavelength might produce different optical dot gain for each ink. In this study, for each primary ink we utilized three different curves obtained by CIEX, Y and Z, which approximately stand for three special wavelength bands, to calculate color coordinates. In addition, we noticed that dot gain curves obtained from the print samples with single ink printed on paper do not work well for the prints where ink is printed on another, or others. Therefore, dot gain curves for different ink superposition situations are optimized by matching the calculated tri-stimulus values of training patches to their measurement counterpoints. For each ink, dividing the dot gain into several dot gain actions responding to different ink superposition situations, we got the final dot gain as a group of multiple curves that takes into account all possible 'dot gain actions' with certain probability coefficients