A Monitor Calibration Model Based on Artificial Neural Network

Abstract

There is a very complicated nonlinear relationship between the input digital image pixel value and the display colors, which is difficult to be described by traditional linear methods to achieve high accuracy. In the study, a monitor calibration model is established based on artificial BP neural network theory and by the hue angle range of the experimental data display classification. Because of the good simulation of nonlinear properties of the BP neural network, the calibration model achieves high accuracy. The color error mean value between the chroma value to be displayed and the chroma value driven by the image pixel value which is calculated by the calibration model is rather less than that of the minimum range of the human eye can identify. The calibration model could be used in the gamut matching phrase in the printing color management system, when the monitor is severed as an output device.