Interactive influences of color attributes on color perception bias

Graphic user interfaces and information visualization use color to represent qualitative or quantitative information. The interaction between adjacent colors leads to perceptual bias, known as simultaneous color contrast, and implicitly distort the understanding of visualized information presentation. To investigate the effect of simultaneous color contrast, we conduct two empirical experiments, in both theoretical and application settings, using a set of random target/proximal combinations of colors in the CIEL* a * b * color space. The perception bias of a target color, induced by its surround, is measured. Linear regression analysis indicates that both a high saturation of the proximal color and a high a */low b * value of the target color cause a strong simultaneous color contrast (i.e., high perception bias). A moderating effect analysis indicates that a * value/ b * value of the target color moderates the influence of the saturation of the proximal color on the perception bias. For example, controlling the saturation of the proximal color, the more reddish/yellowish the target color is, the more alleviated the perceptual bias is.

[1]  C. Ladd Franklin Color Saturation and its Quantitative Relations. , 1896 .

[2]  Thomas J. Whitford,et al.  Romantic Red: Testing the Characteristics of Color–Attraction Effects in a Novel Paradigm , 2017 .

[3]  Ming Ronnier Luo,et al.  CIE 2000 color difference formula: CIEDE2000 , 2002, Other Conferences.

[4]  Nicu Sebe,et al.  Who's Afraid of Itten: Using the Art Theory of Color Combination to Analyze Emotions in Abstract Paintings , 2015, ACM Multimedia.

[5]  J. Bowmaker,et al.  Trichromatic colour vision: why only three receptor channels? , 1983, Trends in Neurosciences.

[6]  Daniel A. Keim,et al.  Methods for Compensating Contrast Effects in Information Visualization , 2014, Comput. Graph. Forum.

[7]  J. D. Mollon,et al.  Kirschmann’s Fourth Law , 2012, Vision Research.

[8]  M. B. Mandler,et al.  Mechanisms of simultaneous color induction. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[9]  Chao Gao,et al.  Object tracking by color distribution fields with adaptive hierarchical structure , 2017, The Visual Computer.

[10]  Edward R. Tufte,et al.  Envisioning Information , 1990 .

[11]  Sivalogeswaran Ratnasingam,et al.  What predicts the strength of simultaneous color contrast? , 2017, Journal of vision.

[12]  Titia Gebuis,et al.  Interactions between colour and synaesthetic colour: An effect of simultaneous colour contrast on synaesthetic colours , 2011, Vision Research.

[13]  Eugène Chevreul,et al.  De la loi du contraste simultané des couleurs et de l'assortiment des objets colorés , 1839 .

[14]  Gabriela Csurka,et al.  Building look & feel concept models from color combinations , 2011, The Visual Computer.

[15]  Mark D. Fairchild,et al.  Color Appearance Models: Fairchild/Color Appearance Models , 2013 .

[16]  Beibei Li,et al.  Color correction based on point clouds alignment in the logarithmic RGB space , 2013, The Visual Computer.

[17]  Alessandro Rizzi,et al.  Colour illusions and the human visual system , 2012 .

[18]  J. Albers,et al.  Interaction of Color , 1971 .

[19]  K. Mullen,et al.  Differential distributions of red–green and blue–yellow cone opponency across the visual field , 2002, Visual Neuroscience.

[20]  L. Maloney,et al.  Color constancy: a method for recovering surface spectral reflectance. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[21]  A. Choudhury Principles of colour perception , 2014 .

[22]  Thomas Wachtler,et al.  "Tilt" in color space: Hue changes induced by chromatic surrounds. , 2015, Journal of vision.

[23]  F. edridge-green Tests for Colour-Blindness , 1895, Nature.

[24]  David E. Irwin,et al.  Visual Search has Memory , 2001, Psychological science.

[25]  Jo Ann S. Kinney,et al.  Factors affecting induced color , 1962 .

[26]  Kaida Xiao,et al.  Color Vision, Opponent Theory , 2015 .

[27]  Matthew O. Ward,et al.  Interactive Data Visualization - Foundations, Techniques, and Applications , 2010 .

[28]  A. Shepherd,et al.  A Vector Model of Colour Contrast in a Cone-Excitation Colour Space , 1997, Perception.

[29]  W. Geisler Adaptation, afterimages and cone saturation , 1978, Vision Research.

[30]  Joshua I. Breier,et al.  Effects of background color on reaction time to stimuli varying in size and contrast: Inferences about human M channels , 1994, Vision Research.

[31]  M. Luo,et al.  The development of the CIE 2000 Colour Difference Formula , 2001 .

[32]  Karen B. Schloss,et al.  Aesthetic response to color combinations: preference, harmony, and similarity , 2010, Attention, perception & psychophysics.

[33]  C. Cierpka,et al.  Particle imaging techniques for volumetric three-component (3D3C) velocity measurements in microfluidics , 2011, Journal of Visualization.

[34]  Francisco Martínez-Verdú,et al.  Computing the Number of Distinguishable Colors under Several Illuminants and Light Sources , 2006, CGIV.

[35]  Patricia A. Chalmers,et al.  The role of cognitive theory in human-computer interface , 2003, Comput. Hum. Behav..

[36]  J. Jacko,et al.  The human-computer interaction handbook: fundamentals, evolving technologies and emerging applications , 2002 .

[37]  Danielle Albers Szafir,et al.  Modeling Color Difference for Visualization Design , 2018, IEEE Transactions on Visualization and Computer Graphics.

[38]  Vidya Setlur,et al.  An Engineering Model for Color Difference as a Function of Size , 2014, CIC.

[39]  Jonathan D. Cohen A Relationalist's Guide to Error About Color Perception , 2007 .