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This work presents a model for dotgain prediction using repetitive patterns based on the characterization of neighboring and clustering effects of a specific printing device. Estimating dotgain is done nowadays by measuring patches of color patterns realized by a specific printing device. Current models use the information about adjacent dots to predict dotgain. However, research has shown that dotgain is influenced by the neighborhood of a dot which in general is bigger than one dot-size, in particular in connection with laser printers. The presented method predicts the dotgain of a dot considering a larger surrounding based on the observation of two main parameters affecting the luminance of a pattern which can be fitted using linear regression.

Dotgain estimation using linear least squares incorporating neighboring and clustering effects