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感知真实世界材料的代表性表面颜色。

Perceiving the representative surface color of real-world materials.

机构信息

Department of Life Sciences, The University of Tokyo, Tokyo, Japan.

出版信息

Sci Rep. 2023 Apr 18;13(1):6300. doi: 10.1038/s41598-023-33563-8.

Abstract

Natural surfaces such as soil, grass, and skin usually involve far more complex and heterogenous structures than the perfectly uniform surfaces assumed in studies on color and material perception. Despite this, we can easily perceive the representative color of these surfaces. Here, we investigated the visual mechanisms underlying the perception of representative surface color using 120 natural images of diverse materials and their statistically synthesized images. Our matching experiments indicated that the perceived representative color revealed was not significantly different from the Portilla-Simoncelli-synthesized images or phase-randomized images except for one sample, even though the perceived shape and material properties were greatly impaired in the synthetic stimuli. The results also showed that the matched representative colors were predictable from the saturation-enhanced color of the brightest point in the image, excluding the high-intensity outliers. The results support the notion that humans judge the representative color and lightness of real-world surfaces depending on simple image measurements.

摘要

自然表面,如土壤、草地和皮肤,通常涉及比颜色和材料感知研究中假设的完全均匀表面更复杂和异质的结构。尽管如此,我们可以轻松地感知这些表面的代表性颜色。在这里,我们使用不同材料的 120 张自然图像及其统计合成图像研究了代表性表面颜色感知背后的视觉机制。我们的匹配实验表明,除了一个样本外,感知到的代表性颜色与 Portilla-Simoncelli 合成图像或相位随机化图像没有显著差异,尽管在合成刺激中,感知到的形状和材料特性受到了很大的损害。结果还表明,匹配的代表性颜色可以根据图像中最亮点的饱和度增强颜色来预测,排除高强度异常值。结果支持这样一种观点,即人类根据简单的图像测量来判断真实表面的代表性颜色和亮度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f880/10113322/664ab8c441c2/41598_2023_33563_Fig1_HTML.jpg

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