A non-device-specific approach to display characterization based on linear, nonlinear, and hybrid search algorithms

In almost all of the recent vision experiments, stimuli are controlled via computers and presented on display devices such as cathode ray tubes (CRTs). Display characterization is a necessary procedure for such computer-aided vision experiments. The standard display characterization called gamma correction and the following linear color transformation procedure are established for CRT displays and widely used in the current vision science field. However, the standard two-step procedure is based on the internal model of CRT display devices, and there is no guarantee as to whether the method is applicable to the other types of display devices such as liquid crystal display and digital light processing. We therefore tested the applicability of the standard method to these kinds of new devices and found that the standard method was not valid for these new devices. To overcome this problem, we provide several novel approaches for vision experiments to characterize display devices, based on linear, nonlinear, and hybrid search algorithms. These approaches never assume any internal models of display devices and will therefore be applicable to any display type. The evaluations and comparisons of chromaticity estimation accuracies based on these new methods with those of the standard procedure proved that our proposed methods largely improved the calibration efficiencies for non-CRT devices. Our proposed methods, together with the standard one, have been implemented in a MATLAB-based integrated graphical user interface software named Mcalibrator2. This software can enhance the accuracy of vision experiments and enable more efficient display characterization procedures. The software is now available publicly for free.