Hyperacuity (scientific term)

The sharpness of our senses is defined by the finest detail we can discriminate. Visual acuity is measured by the smallest letters that can be distinguished on a chart and is governed by the anatomical spacing of the mosaic of sensory elements on the retina. Yet spatial distinctions can be made on a finer scale still: misalignment of borders can be detected with a precision up to 10 times better than visual acuity. This hyperacuity, transcending by far the size limits set by the retinal 'pixels', depends on sophisticated information processing in the brain.

The best example of the distinction between acuity and hyperacuity comes from vision, for example when observing stars on a night sky. The first stage is the optical imaging of the outside world on the retina. Light impinges on the mosaic of receptor sense cells, rods and cones, which covers the retinal surface without gaps or overlap, just like the detecting pixels in the film plane of digital cameras. Each receptor accepts all the light reaching it but acts as a unit, representing a single location in visual space. This compartmentalization sets a limit to the decision whether an image came from a single or a double star (resolution). For a percept of separately articulated stars to emerge, the images of the two must be wide enough apart to leave at least one intervening pixel relatively unstimulated between them. This defines the resolution limit and the basis of visual acuity.

A quite different mechanism operates in hyperacuity, whose quintessential example and the one for which the word was initially coined, is vernier acuity: alignment of two edges or lines can be judged with a precision five or ten times better than acuity. A sophisticated circuitry in the brain identifies the location of a visual feature by assessing the “center of gravity” of the light over several receptors, a task that can be accomplished with much higher precision than the resolution limit set by the receptor spacing. In computer graphics the phrase “sub-pixel resolution” is sometimes used in discussions of anti-aliasing and geometrical superresolution. Though what is in fact involved is not resolution (is it one or two? – a qualitative distinction) but localization (exactly where? – a quantitative judgment) it captures the process. When an image spreads across several pixels, each with graded intensity response but only a single spatial value, the position of the image center can be located more exactly than the width of the pixel, much like the mean of a histogram can be calculated to a fraction of the bin width.

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Wikipedia