Colorimetric Printer Calibration using Modified Sigmoidal Tone-Curve Function

This paper proposes a tone-reproduction method that uses a neural network and modified sigmoid function to perceptually compensate the characteristics of an output device. An inkjet printer was used as the output device the characteristics of which were analyzed by colorimetric measurement. The measured device-characteristic data for primary inks were then used to model the I/O characteristics of the device and a modified sigmoid function was exploited as the optimal tone-reproduction curve for the printer. In the actual application of the printing process, the mapping function between the proposed tone-curve and the input signal of the device was constructed as an LUT and then used as a preprocessor. As a result, the proposed algorithm produced a detailed color reproduction in the mid-tone range and enhanced the image contrast in the shadow-tone regions.