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Image statistics and the perception of surface qualities

Nature volume 447, pages 206–209 (2007)Cite this article

Abstract

The world is full of surfaces, and by looking at them we can judge their material qualities. Properties such as colour or glossiness can help us decide whether a pancake is cooked, or a patch of pavement is icy. Most studies of surface appearance have emphasized textureless matte surfaces1,2,3, but real-world surfaces, which may have gloss and complex mesostructure, are now receiving increased attention4,5,6,7. Their appearance results from a complex interplay of illumination, reflectance and surface geometry, which are difficult to tease apart given an image. If there were simple image statistics that were diagnostic of surface properties it would be sensible to use them8,9,10,11. Here we show that the skewness of the luminance histogram and the skewness of sub-band filter outputs are correlated with surface gloss and inversely correlated with surface albedo (diffuse reflectance). We find evidence that human observers use skewness, or a similar measure of histogram asymmetry, in making judgements about surfaces. When the image of a surface has positively skewed statistics, it tends to appear darker and glossier than a similar surface with lower skewness, and this is true whether the skewness is inherent to the original image or is introduced by digital manipulation. We also find a visual after-effect based on skewness: adaptation to patterns with skewed statistics can alter the apparent lightness and glossiness of surfaces that are subsequently viewed. We suggest that there are neural mechanisms sensitive to skewed statistics, and that their outputs can be used in estimating surface properties.

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Figure 1: These two synthetic images of Michelangelo’s St Matthew sculpture have the same mean luminance.
Figure 2: Perceived lightness and glossiness may be based on the skewness of the luminance histograms.
Figure 3: A proposed neural mechanism for encoding the sub-band skewness by early visual units.
Figure 4: After-effects of perceived lightness and glossiness.

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Acknowledgements

We thank Y. Li for discussions. L.S. and E.H.A. were supported by NTT and by a grant from the National Science Foundation to E.H.A.

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Authors and Affiliations

  1. Human and Information Science Lab, NTT Communication Science Labs, Nippon Telegraph and Telephone Corporation, 3-1 Morinosato-Wakamiya, Atsugi, 243-0198, Japan,

    Isamu Motoyoshi & Shin'ya Nishida

  2. Department of Brain and Cognitive Sciences and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 43 Vassar Street, 46-4115, Cambridge, Massachusetts 02139, USA,

    Lavanya Sharan & Edward H. Adelson

Authors
  1. Isamu Motoyoshi
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  2. Shin'ya Nishida
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  3. Lavanya Sharan
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  4. Edward H. Adelson
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Correspondence to Isamu Motoyoshi.

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Supplementary information

Supplementary Information 1

This file contains Supplementary Figure 1 which is a schematic of the main finding of the study, Supplementary Methods, Supplementary Video Legend which describes how to play the aftereffects demo movies, the Supplementary Data which is divided into four sections titled A through D, and the Supplementary Discussion. Supplementary Data A along with Supplementary Figures 2–4 describe the results for perceived lightness and glossiness for 42 natural surface images. Supplementary Data B and Supplementary Figures 5–8 compare the effects of various image statistics on lightness and glossiness perception. Supplementary Data C and Supplementary Figures 9 and 10 describe the effect of randomizing spatial structures in the image of a surface. Supplementary Data D and Supplementary Figures 11 and 12 contrast the effects of luminance skewness and subband skewness on the perceived lightness and glossiness. Supplementary Discussion and Supplementary Figures 13 and 14 describe the details of the proposed skewness detection mechanism. (PDF 1227 kb)

Supplementary Video 1

This file contains Supplementary Video 1 ‘stucco1’. For further information about the movie please see page 6 of the main Supplementary Information document. (MOV 1348 kb)

Supplementary Video 2

This file contains Supplementary Video 2 ‘stucco2’. For further information about the movie please see page 6 of the main Supplementary Information document. (MOV 1348 kb)

Supplementary Video 3

This file contains Supplementary Video 3 ‘texture1’. For further information about the movie please see page 6 of the main Supplementary Information document. (MOV 1319 kb)

Supplementary Video 4

This file contains Supplementary Video 4 ‘texture 2’. For further information about the movie please see page 6 of the main Supplementary Information document. (MOV 1320 kb)

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Motoyoshi, I., Nishida, S., Sharan, L. et al. Image statistics and the perception of surface qualities. Nature 447, 206–209 (2007). https://doi.org/10.1038/nature05724

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