Beautiful Optical Illusions

Wednesday, August 19, 2009

An optical illusion is characterized by visually perceived images that are deceptive or misleading. Information gathered by the eye is processed by the brain to give a perception that does not tally with a physical measurement of the stimulus source. A conventional assumption is that there are physiological illusions that occur naturally and cognitive illusions that can be demonstrated by specific visual tricks that apparently show particular assumptions in the human perceptual system.
Cognitive illusions are assumed to arise by interaction with in-built assumptions or 'knowledge' of the world, leading to "unconscious inferences", an idea first suggested in the 19th century. Cognitive illusions are commonly divided into ambiguous illusions, distorting illusions, paradox illusions, or fiction illusions.
Ambiguous illusions are pictures or objects that elicit significant changes in appearance. Perception will 'switch' between the alternates as they are considered in turn as available data does not confirm a single view. The Necker cube is a well known example. Another instance is the Rubin vase.
Distorting illusions offer distortions of size, length, or curvature. A striking example is the Café wall illusion. Another example is the famous Mueller-Lyer illusion.
Paradox illusions offer objects that are paradoxical or impossible, such as the Penrose triangle or impossible staircases seen, for example, in the work of M.C. Escher. The triangle is an illusion dependent on a cognitive misunderstanding that adjacent edges must join.
Fiction illusions are the perception of objects that are genuinely not there to all but a single observer, such as those induced by schizophrenia or hallucinogenic drugs.
The explanation of illusions is widely debated. Recent evidence implies that visual illusions are simply the signature of the empirical statistical way all visual percepts are generated. In this interpretation, these phenomena are simply a consequence of the way vision has evolved to solve the inverse problem.


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