Ban Hiroshi, Yamamoto Hiroki
Graduate School of Human and Environmental Studies, Kyoto University, Kyoto, Japan.
J Vis. 2013 May 31;13(6):20. doi: 10.1167/13.6.20.
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.
在几乎所有近期的视觉实验中，刺激都是通过计算机控制，并呈现在诸如阴极射线管（CRT）等显示设备上。显示特性描述是此类计算机辅助视觉实验的必要步骤。针对CRT显示器建立了被称为“伽马校正”的标准显示特性描述以及后续的线性颜色变换程序，并在当前视觉科学领域中广泛使用。然而，标准的两步程序是基于CRT显示设备的内部模型，对于该方法是否适用于其他类型的显示设备（如液晶显示器和数字光处理设备）并无保证。因此，我们测试了标准方法对这类新设备的适用性，发现标准方法对这些新设备无效。为克服这一问题，我们基于线性、非线性和混合搜索算法，提供了几种用于视觉实验以表征显示设备的新颖方法。这些方法从不假定显示设备的任何内部模型，因此将适用于任何显示类型。基于这些新方法与标准程序的色度估计精度的评估和比较证明，我们提出的方法大大提高了非CRT设备的校准效率。我们提出的方法与标准方法一起，已在一个名为Mcalibrator2的基于MATLAB的集成图形用户界面软件中实现。该软件可以提高视觉实验的准确性，并实现更高效的显示特性描述程序。该软件现已免费公开提供。
