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测试迈克尔逊对比度在表面明度感知中的作用。

Testing the role of Michelson contrast for the perception of surface lightness.

作者信息

Wiebel Christiane B, Singh Manish, Maertens Marianne

机构信息

Modelling of Cognitive Processes Group, Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin,

Department of Psychology, Center for Cognitive Science, Rutgers University, New Brunswick, NJ,

出版信息

J Vis. 2016 Sep 1;16(11):17. doi: 10.1167/16.11.17.

Abstract

It is still an unresolved question how the visual system perceives surface lightness given the ambiguity of the sensory input signal. We studied lightness perception using two-dimensional images of variegated checkerboards shown as perspective projections of three-dimensional objects. We manipulated the contrast of a target check relative to its surround either by rendering the image under different viewing conditions or by introducing noncoincidental changes of the reflectance of the surfaces adjacent to the target. We examined the predictive power of the normalized contrast model (Zeiner & Maertens, 2014) for the different viewing conditions (plain view vs. dark and light transparency) as well as for the noncoincidental surround changes (only high or only low reflectances in the surround). The model accounted for lightness matches across different viewing conditions but not for the surround changes. The observed simultaneous contrast effects were smaller than what would be predicted by the model. We evaluated two model extensions that-both relying on contrast-predicted the observed data well. Both model extensions point to the importance of contrast statistics across space and/or time for the computation of lightness, but it awaits future testing to evaluate whether and how the visual system could represent such statistics.

摘要

鉴于感觉输入信号的模糊性,视觉系统如何感知表面亮度仍是一个未解决的问题。我们使用杂色棋盘的二维图像来研究亮度感知,这些图像呈现为三维物体的透视投影。我们通过在不同观察条件下呈现图像,或通过引入与目标相邻表面反射率的非巧合变化,来操纵目标方格相对于其周围环境的对比度。我们研究了归一化对比度模型(Zeiner & Maertens,2014)在不同观察条件(平视与明暗透明度)以及非巧合的周围环境变化(周围环境中只有高反射率或只有低反射率)下的预测能力。该模型解释了不同观察条件下的亮度匹配,但无法解释周围环境的变化。观察到的同时对比效应小于该模型的预测值。我们评估了两个同样依赖对比度的模型扩展,它们对观察数据的预测效果良好。这两个模型扩展都指出了空间和/或时间上的对比度统计对于亮度计算的重要性,但视觉系统是否以及如何表示此类统计数据还有待未来的测试来评估。

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