Perceived glossiness and lightness under real-world illumination.

Color, lightness, and glossiness are perceptual attributes associated with object reflectance. For these perceptual representations to be useful, they must correlate with physical reflectance properties of objects and not be overly affected by changes in illumination or viewing context. We employed a matching paradigm to investigate the perception of lightness and glossiness under geometric changes in illumination. Stimuli were computer simulations of spheres presented on a high-dynamic-range display. Observers adjusted the diffuse and specular reflectance components of a test sphere so that its appearance matched that of a reference sphere simulated under a different light field. Diffuse component matches were close to veridical across geometric changes in light field. In contrast, specular component matches were affected by geometric changes in light field. We tested several independence principles and found (i) that the effect of changing light field geometry on the diffuse component matches was independent of the reference sphere specular component; (ii) that the effect of changing light field geometry on the specular component matches was independent of the reference sphere diffuse component; and (iii) that diffuse and specular components of the match depended only slightly on the roughness of the specular component. Finally, we found that equating simple statistics (i.e., standard deviation, skewness, and kurtosis) computed from the luminance histograms of the spheres did not predict the matches: these statistics differed substantially between spheres that matched in appearance across geometric changes in the light field.

[1]  D. Foster Color constancy , 2011, Vision Research.

[2]  S. Nishida,et al.  Use of image-based information in judgments of surface-reflectance properties. , 1998, Journal of the Optical Society of America. A, Optics, image science, and vision.

[3]  G. Obein,et al.  Difference scaling of gloss: nonlinearity, binocularity, and constancy. , 2004, Journal of vision.

[4]  Peter B. Delahunt,et al.  Does human color constancy incorporate the statistical regularity of natural daylight? , 2004, Journal of vision.

[5]  Wolfgang Heidrich,et al.  High dynamic range display systems , 2004, SIGGRAPH 2004.

[6]  D. B. Judd,et al.  Final Report of the O.S.A. Subcommittee on the Spacing of the Munsell Colors , 1943 .

[7]  B. Wandell,et al.  Asymmetric color matching: how color appearance depends on the illuminant. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[8]  Barton L Anderson,et al.  Image statistics do not explain the perception of gloss and lightness. , 2009, Journal of vision.

[9]  S. Shevell,et al.  Color in complex scenes. , 2008, Annual review of psychology.

[10]  E. Mingolla,et al.  Remote Effects of Highlights on Gloss Perception , 2005, Perception.

[11]  Paul Debevec Rendering synthetic objects into real scenes: bridging traditional and image-based graphics with global illumination and high dynamic range photography , 2008, SIGGRAPH Classes.

[12]  L. Arend,et al.  Simultaneous color constancy: paper with diverse Munsell values. , 1991, Journal of the Optical Society of America. A, Optics and image science.

[13]  Sylvia C. Pont,et al.  A comparison of material and illumination discrimination performance for real rough, real smooth and computer generated smooth spheres , 2005, APGV '05.

[14]  E. Adelson,et al.  Image statistics and the perception of surface qualities , 2007, Nature.

[15]  H. Bülthoff,et al.  Does the brain know the physics of specular reflection? , 1990, Nature.

[16]  Gregory J. Ward,et al.  Measuring and modeling anisotropic reflection , 1992, SIGGRAPH.

[17]  K. Gegenfurtner,et al.  Effects of spatial and temporal context on color categories and color constancy. , 2007, Journal of vision.

[18]  D. Brainard,et al.  Mechanisms of color constancy under nearly natural viewing. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Paul Debevec,et al.  Inverse global illumination: Recovering re?ectance models of real scenes from photographs , 1998 .

[20]  Franz Faul,et al.  Highlight disparity contributes to the authenticity and strength of perceived glossiness. , 2008, Journal of vision.

[21]  Roland W Fleming,et al.  Real-world illumination and the perception of surface reflectance properties. , 2003, Journal of vision.

[22]  H E Smithson,et al.  Sensory, computational and cognitive components of human colour constancy , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[23]  Donald P. Greenberg,et al.  Toward a psychophysically-based light reflection model for image synthesis , 2000, SIGGRAPH.

[24]  Shree K. Nayar,et al.  Generalization of Lambert's reflectance model , 1994, SIGGRAPH.

[25]  Gregory J. Ward,et al.  The RADIANCE lighting simulation and rendering system , 1994, SIGGRAPH.

[26]  David J. Kriegman,et al.  Photometric stereo with non-parametric and spatially-varying reflectance , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[27]  Y. Khoroshaylo,et al.  Colorimetry , 2020, Proceedings of CAOL 2005. Second International Conference on Advanced Optoelectronics and Lasers, 2005..

[28]  S. Pont,et al.  Material — Illumination Ambiguities and the Perception of Solid Objects , 2006, Perception.

[29]  J. Beck,et al.  Highlights and the perception of glossiness , 1981, Perception & psychophysics.

[30]  Shree K. Nayar,et al.  Reflectance and texture of real-world surfaces , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[31]  L. Chalupa,et al.  The visual neurosciences , 2004 .

[32]  Huseyin Boyaci,et al.  Estimating the glossiness transfer function induced by illumination change and testing its transitivity. , 2010, Journal of vision.

[33]  D. Brainard,et al.  Surface gloss and color perception of 3D objects , 2008, Visual Neuroscience.

[34]  Lewis D. Griffin Partitive mixing of images: a tool for investigating pictorial perception , 1999 .

[35]  M. Lucassen,et al.  Color Constancy under Natural and Artificial Illumination , 1996, Vision Research.

[36]  D H Brainard,et al.  Color constancy in the nearly natural image. I. Asymmetric matches. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

[37]  E. Adelson,et al.  Image statistics for surface reflectance perception. , 2008, Journal of the Optical Society of America. A, Optics, image science, and vision.

[38]  Qasim Zaidi,et al.  Colour constancy in context: roles for local adaptation and levels of reference. , 2004, Journal of vision.