Epicoco Déborah, Jonauskaite Domicele, Mohr Christine, Parraga C Alejandro
Institute of Psychology, University of Lausanne, Lausanne, Switzerland.
Faculty of Psychology, University of Vienna, Vienna, Austria.
Iperception. 2024 Sep 15;15(5):20416695241278562. doi: 10.1177/20416695241278562. eCollection 2024 Sep-Oct.
In experimental color research, one must ensure that color is displayed and described reliably. When monitors are involved, colors are displayed through device-dependent color systems. However, these values must be translated into device-independent color systems to interpret what people perceive, often involving techniques such as gamma correction. We sought to explore the feasibility of estimating gamma instead of relying on direct gamma measurements, which typically require specialized equipment like a chromameter. Potential solutions include a computerized perception-based gamma estimation task or adopting the industry-standard gamma value of 2.2. We compared these two solutions against the chromameter measurements in the context of a color-matching task. Thirty-nine participants visually matched red, yellow, green, and blue physical objects using a computerized color picker. Starting from these color choices, we applied two RGB-to-CIE color conversion methods: one using a perception-based gamma estimation and another using the industry-standard gamma. Color values obtained with the chromameter differed from the other two methods by 6-15 JNDs. Small differences existed between the results obtained using the perception-based task and the industry-standard gamma. Thus, we conclude that when standard viewing conditions cannot be assumed, adopting a gamma value of 2.2 should suffice.
在实验性颜色研究中,必须确保颜色能够可靠地显示和描述。当涉及显示器时,颜色通过与设备相关的颜色系统来显示。然而,这些值必须转换为与设备无关的颜色系统,以便解释人们所感知的内容,这通常涉及伽马校正等技术。我们试图探索估计伽马值的可行性,而不是依赖通常需要像色度计这样的专业设备进行的直接伽马测量。潜在的解决方案包括基于感知的计算机化伽马估计任务或采用行业标准的2.2伽马值。我们在颜色匹配任务的背景下,将这两种解决方案与色度计测量结果进行了比较。39名参与者使用计算机化颜色选择器对红色、黄色、绿色和蓝色实物进行视觉匹配。从这些颜色选择开始,我们应用了两种RGB到CIE颜色转换方法:一种使用基于感知的伽马估计,另一种使用行业标准伽马。色度计获得的颜色值与其他两种方法相差6 - 15个最小可觉差。基于感知的任务和行业标准伽马获得的结果之间存在微小差异。因此,我们得出结论,当无法假设标准观看条件时,采用2.2的伽马值应该足够了。