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Transparency and Translucency

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Computer Vision

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Related Concepts

Image Decompositions; Opacity; Transparent Layers

Definition

Transparency is the property of some materials that allows light to be partially transmitted through. The proportion of light a material transmits through determines its transmittance, α. The term “translucency” is generally used in cases where light is transmitted through diffusely.

Background

When a surface is viewed through a partially transmissive material, the optical contributions of the two layers in a given viewing direction are collapsed onto a single intensity in the projected image. If a computer-vision system is to recover the scene correctly, it must be able to decompose or scission the image intensity into the separate contributions of the two material layers (see Fig. 1b).

Transparency and Translucency, Fig. 1
figure 1821 figure 1821

(a) Illustration of the problem of transparency: In each visual direction, the contributions of two distinct layers are collapsed onto a single pixel intensity. These contributions must...

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References

  1. Adelson EH (2000) Lightness perception and lightness illusions. In: Gazzaniga M (ed) The new cognitive neurosciences. MIT, Cambridge, pp 339–351

    Google Scholar 

  2. . Adelson EH, Anandan P (1990) Ordinal characteristics of transparency. In: AAAI-90 workshop on qualitative vision, Boston

    Google Scholar 

  3. Anderson BL (2003) The role of occlusion in the perception of depth, lightness, and opacity. Psychol Rev 110: 762–784

    Article  Google Scholar 

  4. Anderson BL, Singh M, Meng J (2006) The perceived transmittance of inhomogeneous surfaces and media. Vision Res 46:1982–1995

    Article  Google Scholar 

  5. Anderson BL, Winawer J (2008) Layered image representations and the computation of surface lightness. J Vision 8(7):18

    Article  Google Scholar 

  6. Beck J (1985) The perception of transparency in man and machine. Computer Vis Graph Image Process 31: 127–138

    Article  Google Scholar 

  7. Brill MH (1984) Physical and informational constraints on the perception of transparency and translucency. Computer Vis Graph Image Process 28:356–362

    Article  Google Scholar 

  8. D'Zmura M, Colantoni P, Knoblauch K, Laget B (1997) Color transparency. Perception 26:471–492

    Article  Google Scholar 

  9. . Fattal R (2008) Single-image dehazing. In: ACM transactions on graphics (Proceedings of SIGGRAPH), Los Angeles, CA

    Google Scholar 

  10. Faul F, Ekroll V (2002) Psychophysical model of chromatic perceptual transparency based on substractive color mixture. J Opt Soc Am A 19:1084–1095

    Article  Google Scholar 

  11. Gerbino W (1994) Achromatic transparency. In: Gilchrist AL (ed) Lightness, brightness, and transparency. Erlbaum, Hillsdale, pp 215–255

    Google Scholar 

  12. Hagedorn J, D'Zmura M (2000) Color appearance of surfaces viewed through fog. Perception 29: 1169–1184

    Article  Google Scholar 

  13. He K, Sun J, Tang X (2009) Single image haze removal using dark channel prior. Computer Vision and Pattern Recognition in proceeding of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), Miami Beach, FL

    Google Scholar 

  14. . Jensen HW, Marschner SR, Levoy M, Hanrahan P (2001) A practical model for subsurface light transport. In: ACM Transactions on Graphics (Proceedings of SIGGRAPH), Los Angeles, CA, pp 511–518

    Google Scholar 

  15. Metelli F (1974) The perception of transparency. Sci Am 230:90–98

    Article  Google Scholar 

  16. Narasimhan SG, Nayar SK (2003) Contrast restoration of weather-degraded images. IEEE Trans Pattern Anal Mach Intell 25:713–724

    Article  Google Scholar 

  17. Robillotto R, Zaidi Q (2004) Perceived transparency of neutral density filters across dissimilar backgrounds. J Vision 4:183–195

    Article  Google Scholar 

  18. Schechner YY, Narasimhan SG, Nayar SK (2003) Polarization-based vision through haze. Appl Opt 42: 511–525

    Article  Google Scholar 

  19. Singh M, Anderson BL (2002) Toward a perceptual theory of transparency. Psychol Rev 109:492–519

    Article  Google Scholar 

  20. Singh M, Huang X (2003) Computing layered surface representations: an algorithm for detecting and separating transparent overlays. Proc Comput Vis Pattern Recognit (CVPR) 2:11–18

    Google Scholar 

  21. Tan RT (2008) Visibility in bad weather from a single image. Computer vision pattern recognition in proceeding of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, Alaska, USA

    Google Scholar 

  22. Wyszecki G, Stiles WS (1982) Color science: concepts and methods, quantitative data and formulae. Wiley, New York

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Psychology, Rutgers University, Piscataway, NJ, USA

    Manish Singh

Authors
  1. Manish Singh
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Editor information

Editors and Affiliations

  1. Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

    Katsushi Ikeuchi

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Singh, M. (2014). Transparency and Translucency. In: Ikeuchi, K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_559

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