The Role of Real-World Statistical Regularities in Visual Perception

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.