  Why does our visual system fail to reconstruct reality, when we look at
certain patterns? Where do Geometrical illusions start to emerge in the visual
pathway? How far should we take computational models of vision with the same
visual ability to detect illusions as we do? This study addresses these
questions, by focusing on a specific underlying neural mechanism involved in
our visual experiences that affects our final perception. Among many types of
visual illusion, Geometrical and, in particular, Tilt Illusions are rather
important, being characterized by misperception of geometric patterns involving
lines and tiles in combination with contrasting orientation, size or position.
Over the last decade, many new neurophysiological experiments have led to new
insights as to how, when and where retinal processing takes place, and the
encoding nature of the retinal representation that is sent to the cortex for
further processing. Based on these neurobiological discoveries, we provide
computer simulation evidence from modelling retinal ganglion cells responses to
some complex Tilt Illusions, suggesting that the emergence of tilt in these
illusions is partially related to the interaction of multiscale visual
processing performed in the retina. The output of our low-level filtering model
is presented for several types of Tilt Illusion, predicting that the final tilt
percept arises from multiple-scale processing of the Differences of Gaussians
and the perceptual interaction of foreground and background elements. Our
results suggest that this model has a high potential in revealing the
underlying mechanism connecting low-level filtering approaches to mid- and
high-level explanations such as Anchoring theory and Perceptual grouping.
