Developing Calibrating Curves for a Trilinear Interpolation Model During Display Characterization

摘要

Trilinear interpolation is a method of multivariate interpolation on a three-dimensional regular grid. It approximates the value of an intermediate point using data on the lattice points, and thus is frequently used for display characterization with 3D lookup tables (3D LUTs). However, large color errors are usually caused by the nonlinear relationship between the source RGB space and the destination CIELAB space. In this article the display characterization is improved by modifying the traditional trilinear interpolation model. First, the Yule Nielsen n-factor is applied to the destination functions, for the purpose of reducing the nonlinearity between the source and destination color spaces. Afterward, different calibrating curves are developed to calculate the effective values of the source RGB values. The input/source RGB values are usually called nominal values, and the effective values can be regarded as the optimized RGB values which improve the matching degree of the predicted and measured destination CIELAB values. In experiment, a Toshiba M5 liquid crystal display is characterized by using the modified trilinear interpolation model, and the forward and inverse characterization errors of different methods are calculated and compared. The evaluation results demonstrate that both the average and the maximum color errors have significantly decreased when calibrating curve Ill (one of the three types of curves developed) is employed in combination with the optimal n-factor. Thus, the method of developing effective calibrating curves and finding optimal n-factors proposed in this article can be adopted during display characterization. (C) 2016 Society for Imaging Science and Technology.