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亮度与感知透明度。

Lightness and perceptual transparency.

作者信息

Albert Marc K

机构信息

School of Psychology, University of Southampton, Southampton SO17 1BJ, UK.

出版信息

Perception. 2006;35(4):433-43. doi: 10.1068/p5486.

Abstract

To estimate intrinsic descriptors of objects in the environment, effective biological vision systems must 'discount' extrinsic image properties that arise from changes in viewing conditions. In particular, to estimate the reflectance of surfaces, human vision must discount, or 'take account of', likely differences in the illumination of surfaces between one image region and another. If human vision possesses any significant degree of lightness constancy, then we would expect a target perceived to be in low illumination to appear lighter than an identical target perceived to be in higher illumination. In this paper, I present lightness illusions that run directly counter to this expectation. I suggest that mid-level and higher-level factors such as image junction structure and perceived illumination and transparency, are ineffective for generating strong lightness illusions on their own, and that these factors are not 'stronger' than luminance contrast in determining lightness. I discuss the implications of these results for current models of lightness perception. I also suggest a statistical justification for the highest-luminance anchoring rule for lightness.

摘要

为了估计环境中物体的固有特征,有效的生物视觉系统必须“忽略”因观察条件变化而产生的外在图像属性。特别是,为了估计表面的反射率,人类视觉必须忽略或“考虑到”一个图像区域与另一个图像区域之间表面光照可能存在的差异。如果人类视觉具有任何显著程度的明度恒常性,那么我们会预期,一个被感知处于低光照条件下的目标,看起来会比一个被感知处于高光照条件下的相同目标更亮。在本文中,我展示了与这一预期直接相悖的明度错觉。我认为,诸如图像交界结构、感知到的光照和透明度等中级及更高级别的因素,仅凭自身不足以产生强烈的明度错觉,并且在决定明度方面,这些因素并不比亮度对比度“更强”。我讨论了这些结果对当前明度感知模型的影响。我还提出了明度最高亮度锚定规则的统计学依据。

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