Noise masking of White's illusion exposes the weakness of current spatial filtering models of lightness perception.

Spatial filtering models are currently a widely accepted mechanistic account of human lightness perception. Their popularity can be ascribed to two reasons: They correctly predict how human observers perceive a variety of lightness illusions, and the processing steps involved in the models bear an apparent resemblance with known physiological mechanisms at early stages of visual processing. Here, we tested the adequacy of these models by probing their response to stimuli that have been modified by adding narrowband noise. Psychophysically, it has been shown that noise in the range of one to five cycles per degree (cpd) can drastically reduce the strength of some lightness phenomena, while noise outside this range has little or no effect on perceived lightness. Choosing White's illusion (White, 1979) as a test case, we replicated and extended the psychophysical results, and found that none of the spatial filtering models tested was able to reproduce the spatial frequency specific effect of narrowband noise. We discuss the reasons for failure for each model individually, but we argue that the failure is indicative of the general inadequacy of this class of spatial filtering models. Given the present evidence we do not believe that spatial filtering models capture the mechanisms that are responsible for producing many of the lightness phenomena observed in human perception. Instead we think that our findings support the idea that low-level contributions to perceived lightness are primarily determined by the luminance contrast at surface boundaries.

[1]  Ernst Mach,et al.  The analysis of sensations and the relation of the physical to the psychical , 1914, The Mathematical Gazette.

[2]  W. Benary,et al.  Beobachtungen zu einem Experiment über Helligkeitskontrast , 1924 .

[3]  H. Wallach Brightness constancy and the nature of achromatic colors. , 1948, Journal of experimental psychology.

[4]  Vivian O'Brien,et al.  Contour Perception, Illusion and Reality* , 1958 .

[5]  K. Craik The nature of psychology , 1966 .

[6]  R. M. Shapley,et al.  Edge detectors in human vision , 1973, The Journal of physiology.

[7]  R. Haber,et al.  Visual Perception , 2018, Encyclopedia of Database Systems.

[8]  M. White,et al.  A New Effect of Pattern on Perceived Lightness , 1979, Perception.

[9]  A. Gilchrist,et al.  When does perceived lightness depend on perceived spatial arrangement? , 1980, Perception & psychophysics.

[10]  R. Watt,et al.  A theory of the primitive spatial code in human vision , 1985, Vision Research.

[11]  S. Grossberg,et al.  Neural dynamics of 1-D and 2-D brightness perception: A unified model of classical and recent phenomena , 1988, Perception & psychophysics.

[12]  D. Burr,et al.  Feature detection in human vision: a phase-dependent energy model , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[13]  D. Knill,et al.  Apparent surface curvature affects lightness perception , 1991, Nature.

[14]  F. Kingdom,et al.  A multi-channel approach to brightness coding , 1992, Vision Research.

[15]  Denis G. Pelli,et al.  The visual filter mediating letter identification , 1994, Nature.

[16]  R. Taya,et al.  Varying the Strength of the Munker—White Effect by Stereoscopic Viewing , 1995, Perception.

[17]  B. Anderson A Theory of Illusory Lightness and Transparency in Monocular and Binocular Images: The Role of Contour Junctions , 1997, Perception.

[18]  M. McCourt,et al.  A multiscale spatial filtering account of the White effect, simultaneous brightness contrast and grating induction , 1999, Vision Research.

[19]  S. Grossberg,et al.  Neural dynamics of 3-D surface perception: Figure-ground separation and lightness perception , 2000, Perception & psychophysics.

[20]  Marina G Bloj,et al.  An Empirical Study of the Traditional Mach Card Effect , 2002, Perception.

[21]  S. Dakin,et al.  Natural image statistics mediate brightness ‘filling in’ , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[22]  Hong Zhou,et al.  Searching For The Neural Mechanism Of Color Filling-In , 2003 .

[23]  Nicolai Petkov,et al.  Suppression of contour perception by band-limited noise and its relation to nonclassical receptive field inhibition , 2003, Biological cybernetics.

[24]  M. McCourt,et al.  A unified theory of brightness contrast and assimilation incorporating oriented multiscale spatial filtering and contrast normalization , 2004, Vision Research.

[25]  P. Laurinen,et al.  Spatial frequency tuning of brightness polarity identification. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.

[26]  M. Rudd,et al.  The highest luminance anchoring rule in achromatic color perception: some counterexamples and an alternative theory. , 2005, Journal of vision.

[27]  A. AlanGilchrist Seeing in Black and White , 2006 .

[28]  Alan E. Robinson,et al.  Explaining brightness illusions using spatial filtering and local response normalization , 2007, Vision Research.

[29]  R. Lotto,et al.  What Are Lightness Illusions and Why Do We See Them? , 2007, PLoS Comput. Biol..

[30]  M. Morrone,et al.  The lowest spatial frequency channel determines brightness perception , 2007, Vision Research.

[31]  M. Vanrell,et al.  Multiresolution wavelet framework models brightness induction effects , 2008, Vision Research.

[32]  P. Laurinen,et al.  Low-level features determine brightness in White’s and Benary’s illusions , 2009, Vision Research.

[33]  Aapo Hyvärinen,et al.  Visual Features Underlying Perceived Brightness as Revealed by Classification Images , 2009, PloS one.

[34]  D. Todorović,et al.  Adjacency and surroundedness in the depth effect on lightness. , 2010, Journal of vision.

[35]  Frederick A.A. Kingdom,et al.  Lightness, brightness and transparency: A quarter century of new ideas, captivating demonstrations and unrelenting controversy , 2011, Vision Research.

[36]  Mariann Hudák,et al.  Changing the Chevreul Illusion by a Background Luminance Ramp: Lateral Inhibition Fails at Its Traditional Stronghold - A Psychophysical Refutation , 2011, PloS one.

[37]  David M. Kaplan,et al.  The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective* , 2011, Philosophy of Science.

[38]  Sarah R. Allred,et al.  Lightness perception in high dynamic range images: local and remote luminance effects. , 2012, Journal of vision.

[39]  Alan E. Robinson,et al.  Dynamic brightness induction causes flicker adaptation, but only along the edges: evidence against the neural filling-in of brightness. , 2013, Journal of vision.

[40]  S. Anstis Contour adaptation. , 2013, Journal of vision.

[41]  M. Rudd Edge integration in achromatic color perception and the lightness-darkness asymmetry. , 2013, Journal of vision.

[42]  Hamutal Slovin,et al.  A Contrast and Surface Code Explains Complex Responses to Black and White Stimuli in V1 , 2014, The Journal of Neuroscience.

[43]  Michael E. Rudd,et al.  A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences , 2014, Front. Hum. Neurosci..

[44]  R. Shapley,et al.  Context affects lightness at the level of surfaces. , 2013, Journal of vision.

[45]  Felix A Wichmann,et al.  Testing the role of luminance edges in White's illusion with contour adaptation. , 2015, Journal of vision.