Image credit: Public domain
We perceive the visual world as made of objects of different shapes, sizes and colors. Some may be smooth, shiny and reflective, whereas others are rough and uneven; some may be in shadow, while others are brightly lit. The brain must identify and distinguish all of these different features to build an accurate, three-dimensional model of the environment.
Information about any visual feature originates as light bouncing off an object and entering the eye, which then captures the reflected light and focuses it onto the retina. There, cells generate electrical signals for the brain to process. However, different types of visual features can result in the same pattern of activity. The brain must rely on prior knowledge and educated guesses to disentangle the contributions made by different features, but we know little about the processes that make this possible.
Here, Mooney et al. examine how the visual system can tell whether an object is blurry, or if it presents the smooth light-to-dark shading that can accompany curved shapes. The experiments show that images of shaded curved surfaces can appear blurry even when they are fully in focus. However, adding a specific type of sharp edge, called a bounding contour, eliminates this illusion. This suggests that the brain uses these sharp edges to judge whether an image is in focus. In fact, adding bounding contours can trick the visual system into perceiving a blurry image as sharp.
Understanding how the human visual system interprets images could lead to advances in computer vision. Artificial vision systems – such as those used in face or license plate recognition – must determine which parts of an image are in focus before attempting to extract visual information. Identifying the cues that enable the human visual system to solve this problem could help to train computers to do the same.
