Multiple models of vision propose that perception involves a process of prediction and verification. Here we argue that real-world statistical regularities—representations that, on average, more quickly make contact with meaning—serve as the basis of these predictions. We show that statistically regular images—those, we argue, that more closely match perceptual predictions—are more readily perceived and more efficiently processed than statistically irregular images.

中文翻译：

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现实世界统计规律在视觉感知中的作用


多种视觉模型表明，感知涉及预测和验证的过程。在这里，我们认为现实世界的统计规律——平均而言，更快地与意义联系的表示——是这些预测的基础。我们表明，统计上规则的图像（我们认为这些图像与感知预测更匹配）比统计上不规则的图像更容易被感知并且更有效地处理。