Did you know? Visual adaption causing illusion (2016)

Dynamic range, that is the ratio of the largest to smallest values of a quantity, is a crucial characteristic of a sensory system. Our eyes outperform all known biological and technical sensors by orders of magnitude! The dark-adapted eye is capable of detecting few single photons (Barlow 1956), whereas vision is also possible in bright sunlight at the beach or when looking at sun-illuminated clouds where we find more than 1012 higher light intensities (luminosity). In analogy, imagine a handy ruler of measuring in the millimetre range as well as lengths in the order of the earth moon distance. The physical dynamic range of a classic photograph or painting is only in the order of 102. If an artist wishes to depict huge dynamic range of, for instance, low intensity of a natural night scenery together with comparable very bright structures of the moon on a painting, the artist has to ‘compress’ the dynamic range (Fig. 1A). This is ‘easy’ for the artist as this type of compression is accomplished by the artist's visual perception. Photographers use the so-called high-dynamic-range photography which in essence does a mathematical defined mapping of large dynamic range to a smaller dynamic range that in turn can then be displayed on a photographic print or a computer screen. The relatively small dynamic range of the camera chip is expanded by multiple exposures with different exposure times. This works, of course, only for non-moving objects. To overcome this drawback, some camera chips consist of pixels with different sensitivity to obtain a larger dynamic range. The mathematical trick of the algorithms that compress the large dynamic range for display on a screen or on a printout is to maintain local object contrasts and to diminish global contrasts (Fig. 1B). Multiple algorithms exist in the literature to accomplish that (Debevec & Malik 1997, Fattal et al. 2002, Reinhard et al. 2002). By these techniques, it is possible to simultaneously show high contrasts, for instance the illuminated paintings on a lead crystal church window together with details of objects in the dark sanctuary on the same photograph that would be impossible by classical photography. The human vision is complex, combining fast pupil reaction and slower biochemical brightness adaptation leading to an adjustment depending of the average brightness of the local object looked at. So the human vision can perfectly deal with the situation of the tremendous intensity differences between the windows and the dark areas of the sanctuary. This adaptation is also colour-selective and thus may lead to strange colour impressions. For example, while climbing the Grand Canyon, red-sensitive cones bleach overproportion leading to less sensitivity for red. Looking under these circumstances at someone's blond hair reflecting white sunlight causes a blue-greenish impression. Visual adaptation, in general, allows assessing vast spatial information encoded in the contrast signal, to effectively identify structures of objects such as trees and bushes, while we wander in the midst of darkness. However, the downside of visual adaption is that our visual perception often fails in measuring absolute intensity that is required for scientific densitometry for accurate estimation of grey levels, or of colour intensity in a histological staining. This is true for images that are looked at in a consecutive manner and also even for grey levels that are depicted in one and the same image. Take a grey bar of a unique grey level in front of a grey gradient: the bar is perceived also as a gradient in the opposite direction (Fig. 1C). The same holds for colour impression when the physically defined identical colour is shown in different colour contexts. It is then perceived as multiple distinct colours. Keeping this in mind, we should avoid visual scores to quantify physical or chemical or biochemical outcomes of experiments and should apply, for instance, optical densitometry for measuring those entities. The huge adaptation capacity of the visual system is one prerequisite for the optimized detection of local spatial contrasts. This optimization, however, has a tribute. It may lead to illusions, for example the so-called Mach band illusions where the small difference in grey levels is exaggerated once the two areas touch each other by enhancing the ‘edge’ between the two almost identical areas. This is relevant to know as it may lead to potential misinterpretation of X-ray images (Nielsen 2001, Panikkath & Panikkath 2014). None.