Aesthetic Evaluation of Digitally Reproduced Art Images

Most people encounter art images as digital reproductions on a computer screen instead of as originals in a museum or gallery. With the development of digital technologies, high-resolution artworks can be accessed anywhere and anytime by a large number of viewers. Since these digital images depict the same content and are attributed to the same artist as the original, it is often implicitly assumed that their aesthetic evaluation will be similar. When it comes to the digital reproductions of art, however, it is also obvious that reproductions do differ from the originals in various aspects. Besides image quality, resolution, and format, the most obvious change is in the representation of color. The effects of subjectively varying surface-level image features on art evaluation have not been clearly assessed. To address this gap, we compare the evaluation of digital reproductions of 16 expressionist and impressionist paintings manipulated to have a high color saturation vs. a saturation similar to the original. We also investigate the impact of viewing time (100 ms vs. unrestricted viewing time) and expertise (art experts vs. laypersons), two other aspects that may impact the perception of art in online contexts. Moreover, we link these dimensions to a recent model of aesthetic experience [the Vienna Integrated Model of Top-Down and Bottom-Up Processes in Art Perception (VIMAP)]. Results suggest that color saturation does not exert a major influence on liking. Cognitive and emotional aspects (interest, confusion, surprise, and boredom), however, are affected – to different extents for experts and laypersons. For laypersons, the increase in color saturation led to more positive assessments of an artwork, whereas it resulted in increased confusion for art experts. This insight is particularly important when it comes to reproducing artworks digitally. Depending on the intended use, increasing or decreasing the color saturation of the digitally reproduced image might be most appropriate. We conclude with a discussion of these findings and address the question of why empirical aesthetics requires more precise dimensions to better understand the subtle processes that take place in the perception of today’s digitally reproduced art environment.

[1]  Rudolf Arnheim,et al.  Kunst und Sehen : eine Psychologie des schöpferischen Auges , 1965 .

[2]  H. Eysenck Personal preferences, aesthetic sensitivity and personality in trained and untrained subjects. , 1972, Journal of personality.

[3]  J. Russell A circumplex model of affect. , 1980 .

[4]  Robin N. Strickland,et al.  Digital Color Image Enhancement Based On The Saturation Component , 1987 .

[5]  Gerald C. Cupchik,et al.  The evaluation of high art and popular art by naive and experienced viewers. , 1992 .

[6]  Jacob Cohen,et al.  A power primer. , 1992, Psychological bulletin.

[7]  P. Valdez,et al.  Effects of color on emotions. , 1994, Journal of experimental psychology. General.

[8]  J.J. Rodriguez,et al.  Efficient luminance and saturation processing techniques for bypassing color coordinate transformations , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[9]  H. Ridder,et al.  Chroma variations and perceived quality of color images of natural scenes , 1997 .

[10]  Lisa F. Smith,et al.  Original Paintings versus Slide and Computer Reproductions: A Comparison of Viewer Responses , 1999 .

[11]  Lisa F. Smith,et al.  The Influence of Presentation Format and Viewer Training in the Visual Arts on the Perception of Pictorial and Aesthetic Qualities of Paintings , 2001, Perception.

[12]  Roy S. Berns,et al.  The Science of Digitizing Paintings for Color-Accurate Image Archives : A Review , 2001 .

[13]  N. Camgoz,et al.  Effects of Hue, Saturation, and Brightness on Preference , 2002 .

[14]  T. Jacobsen,et al.  Temporal Stability and Consistency of Aesthetic Judgments of Beauty of Formal Graphic Patterns , 2003, Perceptual and motor skills.

[15]  H. Leder,et al.  A model of aesthetic appreciation and aesthetic judgments. , 2004, British journal of psychology.

[16]  N. Camgoz,et al.  Effects of Hue, Saturation, and Brightness: Part 2: Attention. , 2004 .

[17]  Kar Yan Tam,et al.  Designing product listing pages on e-commerce websites: an examination of presentation mode and information format , 2004, Int. J. Hum. Comput. Stud..

[18]  Personal preferences, aesthetic sensitivity and personality in trained and untrained subjects , 2004 .

[19]  P. Locher,et al.  A Comparison of the Perceived Pictorial and Aesthetic Qualities of Original Paintings and Their Postcard Images , 2004 .

[20]  N. Schwarz,et al.  Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver's Processing Experience? , 2004, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

[21]  J. Ezrati,et al.  PAINTING VIEWED UNDER DIFFERENT ILLUMINANTS: DOES IT CHANGE THE MEANING? , 2006 .

[22]  Françoise Viénot,et al.  Color Enhancement of Digital Images by Experts and Preference Judgments by Observers , 2006 .

[23]  Lisa F. Smith,et al.  Effects of Time and Information on Perception of Art , 2006 .

[24]  Gitte Lindgaard,et al.  Attention web designers: You have 50 milliseconds to make a good first impression! , 2006, Behav. Inf. Technol..

[25]  Claus-Christian Carbon,et al.  Style follows content: on the microgenesis of art perception. , 2008, Acta psychologica.

[26]  Charles E. Osgood,et al.  Semantic Differential Technique in the Comparative Study of Cultures1 , 2009 .

[27]  Pablo P. L. Tinio,et al.  Natural Scenes Are Indeed Preferred, but Image Quality Might Have the Last Word , 2009 .

[28]  William R. King,et al.  Association for Information Systems (AIS) , 2010 .

[29]  Ann H. Harvey,et al.  Domain expertise insulates against judgment bias by monetary favors through a modulation of ventromedial prefrontal cortex , 2011, Proceedings of the National Academy of Sciences.

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

[31]  E Standard,et al.  Statistik für Sozialwissenschaftler , 2012 .

[32]  Alexandre N. Tuch,et al.  The role of visual complexity and prototypicality regarding first impression of websites: Working towards understanding aesthetic judgments , 2012, Int. J. Hum. Comput. Stud..

[33]  P. Silvia Interested Experts, Confused Novices: Art Expertise and the Knowledge Emotions , 2013 .

[34]  Katharina Reinecke,et al.  Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness , 2013, CHI.

[35]  Karen B. Schloss,et al.  Visual aesthetics and human preference. , 2013, Annual review of psychology.

[36]  Xin Li,et al.  The Impact of Product Photo on Online Consumer Purchase Intention: an Image-Processing Enabled Empirical Study , 2014, PACIS.

[37]  Alexandre N. Tuch,et al.  Linking objective design factors with subjective aesthetics: An experimental study on how structure and color of websites affect the facets of users' visual aesthetic perception , 2015, Comput. Hum. Behav..

[38]  Jan R. Landwehr,et al.  A Dual-Process Perspective on Fluency-Based Aesthetics , 2015, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

[39]  Steve Nebel,et al.  The negative impact of saturation on website trustworthiness and appeal: A temporal model of aesthetic website perception , 2016, Comput. Hum. Behav..

[40]  H. Leder,et al.  Visualizing the Impact of Art: An Update and Comparison of Current Psychological Models of Art Experience , 2016, Front. Hum. Neurosci..

[41]  R. Pownall,et al.  Pricing Color Intensity and lightness in Contemporary Art Auctions , 2016 .

[42]  H. Leder,et al.  Move me, astonish me… delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates. , 2017, Physics of life reviews.

[43]  Michael Eid,et al.  Measuring aesthetic emotions: A review of the literature and a new assessment tool , 2017, PloS one.

[44]  Catarina A. R. João,et al.  The colors of paintings and viewers’ preferences , 2017, Vision Research.

[45]  N. V. Dongen,et al.  The science of art: The universality of the law of contrast , 2017 .

[46]  J. Wagemans,et al.  Beauty in the blink of an eye: The time course of aesthetic experiences , 2018, British journal of psychology.

[47]  H. Leder,et al.  More than the sum of its parts: Perceiving complexity in painting. , 2018, Psychology of Aesthetics, Creativity, and the Arts.

[48]  V. Gallese,et al.  Behavioral and autonomic responses to real and digital reproductions of works of art. , 2018, Progress in brain research.

[49]  Helmut Leder,et al.  Symmetry Is Not a Universal Law of Beauty , 2018, Empirical Studies of the Arts.

[50]  Ulrich Ansorge,et al.  Implicit and Explicit Evaluation of Visual Symmetry as a Function of Art Expertise , 2018, i-Perception.

[51]  K. Opwis,et al.  Impact of contextualizing information on aesthetic experience and psychophysiological responses to art in a museum: A naturalistic randomized controlled trial. , 2019 .

[52]  Helmut Leder,et al.  Does Gallery Lighting Really Have an Impact on Appreciation of Art? An Ecologically Valid Study of Lighting Changes and the Assessment and Emotional Experience With Representational and Abstract Paintings , 2019, Front. Psychol..

[53]  H. Leder,et al.  The kitsch switch—or (when) do experts dislike Thomas Kinkade art? A study of time-based evaluation changes in top-down versus bottom-up assessment. , 2020 .

[54]  Karen B. Schloss,et al.  Color Preference , 2020 .

[55]  H. Leder,et al.  The Vienna Art Interest and Art Knowledge Questionnaire (VAIAK): A unified and validated measure of art interest and art knowledge. , 2020 .