A tool to create illuminant and reflectance spectra for light-driven graphics and visualization

ABSTRACT

Full spectra allow the generation of a physically correct rendering of a scene under different lighting conditions. In this article we devise a tool to augment a palette of given lights and material reflectances with constructed spectra, yielding specified colors or spectral properties such as metamerism or objective color constancy. We utilize this to emphasize or hide parts of a scene by matching or differentiating colors under different illuminations. These color criteria are expressed as a quadratic programming problem, which may be solved with positivity constraints. Further, we characterize full spectra of lights, surfaces, and transmissive materials in an efficient linear subspace model by forming eigenvectors of sets of spectra and transform them to an intermediate space in which spectral interactions reduce to simple component-wise multiplications during rendering. The proposed method enhances the user's freedom in designing photo-realistic scenes and helps in creating expressive visualizations. A key application of our technique is to use specific spectral lighting to scale the visual complexity of a scene by controlling visibility of texture details in surface graphics or material details in volume rendering.

REFERENCES

• 1: Abdul-Rahman, A. and Chen, M. 2005. Spectral volume rendering based on the Kubelka-Munk theory. Comput. Graph. Forum 24, 3, 413--422.
• 2: Anderson, M., Motta, R., Chandrasekarand, S., and Stokes, M. 1996. Proposal for a standard default color space for the Internet—sRGB. In Proceedings of the 4th Joint Conference on Color Imaging Color, Science, Systems and Applications. Society for Imaging Science & Technology (IS&T)/Society for Information Display (SID), 238--245.
• 3: Steven Bergner , Torsten Möller , Mark S. Drew , Graham D. Finlayson, Interactive spectral volume rendering, Proceedings of the conference on Visualization '02, October 27-November 01, 2002, Boston, Massachusetts
• 4: Steven Bergner , Torsten Moller , Melanie Tory , Mark S. Drew, A Practical Approach to Spectral Volume Rendering, IEEE Transactions on Visualization and Computer Graphics, v.11 n.2, p.207-216, March 2005 [doi>10.1109/TVCG.2005.19]
• 5: Borges, C. 1991. Trichromatic approximation method for surface illumination. J. Opt. Soc. Amer. A 8, 1319--1323.
• 6: Devlin, K., Chalmers, A., Wilkie, A., and Purgathofer, W. 2002. Star: Tone reproduction and physically based spectral rendering. In State of the Art Reports. Proceedings of the Eurographics, D. Fellner and R. Scopignio, eds. The Eurographics Association, 101--123.
• 7: Craig Donner , Henrik Wann Jensen, A spectral shading model for human skin, ACM SIGGRAPH 2006 Sketches, July 30-August 03, 2006, Boston, Massachusetts [doi>10.1145/1179849.1180033]
• 8: Drew, M. S. and Finlayson, G. D. 2000. Spectral sharpening with positivity. J. Opt. Soc. Amer. A 17, 1361--1370.
• 9: Drew, M. S. and Finlayson, G. D. 2002. Multispectral processing without spectra. Tech. rep. SFU-CMPT-03/02-TR2002-02, Simon Fraser University School of Computing Science. March. Also: Representation of colour in a colour display system, UK patent application No. 0206916.9. Under review, British Patent Office.
• 10: Drew, M. S. and Finlayson, G. D. 2003. Multispectral processing without spectra. J. Opt. Soc. Amer. A 20, 7, 1181--1193.
• 11: Mark S. Drew , Brian V. Funt, Natural metamers, CVGIP: Image Understanding, v.56 n.2, p.139-151, Sept. 1992 [doi>10.1016/1049-9660(92)90036-3]
• 12: Farrell, J., Cupitt, J., Saunders, D., and Wandell, B. 1999. Estimating spectral reflectances of digital artwork. In Chiba Conference of Multispectral Imaging.
• 13: Finlayson, G. D., Drew, M. S., and Funt, B. V. 1994. Spectral sharpening: Sensor transformations for improved color constancy. J. Opt. Soc. Amer. A 11, 5, 1553--1563.
• 14: Andrew S. Glassner, How to Derive a Spectrum from an RGB Triplet, IEEE Computer Graphics and Applications, v.9 n.4, p.95-99, July 1989 [doi>10.1109/38.31468]
• 15: Jay S. Gondek , Gary W. Meyer , Jonathan G. Newman, Wavelength dependent reflectance functions, Proceedings of the 21st annual conference on Computer graphics and interactive techniques, p.213-220, July 1994 [doi>10.1145/192161.192202]
• 16: Pat Hanrahan , Wolfgang Krueger, Reflection from layered surfaces due to subsurface scattering, Proceedings of the 20th annual conference on Computer graphics and interactive techniques, p.165-174, August 02-06, 1993, Anaheim, CA [doi>10.1145/166117.166139]
• 17: Harrower, M. A. and Brewer, C. A. 2003. Colorbrewer.org: An online tool for selecting color schemes for maps. The Cartograph. J. 40, 1, 27--37. http://www.colorbrewer.org.
• 18: Garrett M. Johnson , Mark D. Fairchild, Full-Spectral Color Calculations in Realistic Image Synthesis, IEEE Computer Graphics and Applications, v.19 n.4, p.47-53, July 1999 [doi>10.1109/38.773963]
• 19: Marimont, D. H. and Wandell, B. A. 1992. Linear models of surface and illuminant spectra. J. Opt. Soc. Amer. A 11, 1905--1913.
• 20: Wojciech Matusik , Hanspeter Pfister , Matt Brand , Leonard McMillan, A data-driven reflectance model, ACM Transactions on Graphics (TOG), v.22 n.3, July 2003
• 21: Herke Jan Noordmans , Hans T. M. van der Voort , Arnold W. M. Smeulders, Spectral Volume Rendering, IEEE Transactions on Visualization and Computer Graphics, v.6 n.3, p.196-207, July 2000 [doi>10.1109/2945.879782]
• 22: Mark S. Peercy, Linear color representations for full speed spectral rendering, Proceedings of the 20th annual conference on Computer graphics and interactive techniques, p.191-198, August 02-06, 1993, Anaheim, CA [doi>10.1145/166117.166142]
• 23: Mark S. Peercy , Benjamin M. Zhu , Daniel R. Baum, Interactive full spectral rendering, Proceedings of the 1995 symposium on Interactive 3D graphics, p.67-ff., April 09-12, 1995, Monterey, California, United States [doi>10.1145/199404.199415]
• 24: Matt Pharr , Greg Humphreys, Physically Based Rendering: From Theory to Implementation, Morgan Kaufmann Publishers Inc., San Francisco, CA, 2004
• 25: Sharma, G. and Trussell, H. 1997. Figures of merit for color scanners. IEEE Trans. Image Proc. 6, 7, 990--1001.
• 26: Brian Smits, An RGB-to-spectrum conversion for reflectances, Journal of Graphics Tools, v.4 n.4, p.11-22, 1999
• 27: Jos Stam, Diffraction shaders, Proceedings of the 26th annual conference on Computer graphics and interactive techniques, p.101-110, July 1999 [doi>10.1145/311535.311546]
• 28: Strengert, M., Klein, T., Botchen, R., Stegmaier, S., Chen, M., and Ertl, T. 2006. Spectral volume rendering using GPU-based raycasting. The Visual Comput. 22, 8.
• 29: Yinlong Sun , F. David Fracchia , Thomas W. Calvert , Mark S. Drew, Deriving Spectra from Colors and Rendering Light Interference, IEEE Computer Graphics and Applications, v.19 n.4, p.61-67, July 1999 [doi>10.1109/38.773965]
• 30: Sun, Y., Fracchia, F. D., and Drew, M. S. 2000. Rendering diamonds. In Proceedings of the Western Computer Graphics Symposium, 9--15.
• 31: Wang, Q., Xy, H., and Sun, Y. 2004. Practical construction of reflectances for spectral rendering. In Proceedings of the Winter School of Computer Graphics Posters.
• 32: Wyszecki, G. and Stiles, W. 1982. Color Science: Concepts and Methods, Quantitative Data and Formulas, 2nd ed. Wiley, New York.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.7 Three-Dimensional Graphics and Realism
          Subjects: Color, shading, shadowing, and texture

Additional Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Quadratic programming methods

  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.5 Computational Geometry and Object Modeling
          Subjects: Physically based modeling

General Terms:
Algorithms, Design

Keywords:
Spectral light and reflectance design, linear spectral color models