Tone reproduction technique using neural network in inkjet printers

The paper proposes a tone reproduction method using neural network and sigmoid function to perceptually compensate for the characteristics of an output device. The printer was used as an output device and its characteristics were analyzed by colorimetric measurement. The measured device characteristics were used in the learning process of a neural network which modeled the I/O characteristics of the device and the sigmoid function was exploited for optimal tone reproduction curves for the printer. In the application of real images, the mapping function between the proposed tone-curve and input signal of each device was built as a LUT (look-up table) between sigmoid function input to the neural network and output of the neural network. As a result, the proposed algorithms showed detailed color reproduction and enhanced image contrast on the printer