OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 4, Iss. 9 — Sep. 4, 2009

Trichromatic red–green–blue camera used for the recovery of albedo and reflectance of rough-textured surfaces under different illumination conditions

Clara Plata, Juan Luis Nieves, Eva M. Valero, and Javier Romero  »View Author Affiliations


Applied Optics, Vol. 48, Issue 19, pp. 3643-3653 (2009)
http://dx.doi.org/10.1364/AO.48.003643


View Full Text Article

Enhanced HTML    Acrobat PDF (1112 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Photometric-stereo techniques are based on the fact that image intensity depends upon the orientation of the surface with regard to the source of the illumination and its spectral reflectance. They are of special interest when dealing with rough surfaces because they usually present shadowed regions where sudden illumination changes might be found. In the present work we introduce an extension of the four-source photometric-stereo algorithm to color images that is able to recover the surface spectral reflectance of objects captured with a red–green–blue (RGB) camera. This method allows image rendering, even for rough-textured surfaces, under different directions of the impinging illumination. In addition, the introduction of spectral recovery techniques applied to the albedo and spectral reflectance from rough surfaces offers the possibility of image rendering for scenes captured under sources of illumination differing in spectral distribution. Using albedo instead of RGB information helps to avoid any shadows or highlights that might falsify results. One of the advantages of this spectral-based photometric-stereo method is that it can recover not only the albedo values, but also the spectral reflectance spectrum of an object’s surface on a pixel-by-pixel basis, as can be done with more complex hyperspectral imaging devices involving a camera coupled to an extensive set of narrowband filters.

© 2009 Optical Society of America

OCIS Codes
(330.1690) Vision, color, and visual optics : Color
(330.1730) Vision, color, and visual optics : Colorimetry

ToC Category:
Vision, Color, and Visual Optics

History
Original Manuscript: February 18, 2009
Revised Manuscript: May 8, 2009
Manuscript Accepted: June 3, 2009
Published: June 22, 2009

Virtual Issues
Vol. 4, Iss. 9 Virtual Journal for Biomedical Optics

Citation
Clara Plata, Juan Luis Nieves, Eva M. Valero, and Javier Romero, "Trichromatic red-green-blue camera used for the recovery of albedo and reflectance of rough-textured surfaces under different illumination conditions," Appl. Opt. 48, 3643-3653 (2009)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-48-19-3643


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. B. A. Wandell, “The synthesis and analysis of color images,” IEEE Trans. Pattern Anal. Machine Intell. pami-9, 2-13 (1987). [CrossRef]
  2. J. Hardeberg, F. Schmidtt, H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532-2548 (2002). [CrossRef]
  3. F. H. Imai and R. Berns, “Spectral estimation using trichromatic digital cameras,” in International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42-49.
  4. N. Shimano, “Evaluation of a multispectral image acquisition system aimed at reconstruction of spectral reflectances,” Opt. Eng. 44, 107005 (2005). [CrossRef]
  5. E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera and colored filters,” Color Res. Appl. 32, 352-360 (2007). [CrossRef]
  6. S. M. C. Nascimento, F. P. Ferreira, and D. H. Foster, “Statistics of spatial cone excitation ratios in natural scenes,” J. Opt. Soc. Am. A 19, 1484-1490 (2002). [CrossRef]
  7. J. L. Nieves, E. M. Valero, S. M. C. Nascimento, J. Hernández-Andrés, and J. Romero “Multispectral synthesis of daylight using a commercial digital CCD camera,” Appl. Opt. 44, 5696-5703 (2005). [CrossRef] [PubMed]
  8. C. Plata, J. L. Nieves, and J. Romero, “Combining spectral and photometric stereo techniques for reflectance estimation using an RGB digital camera,” in Color in Graphics, Imaging and Vision (CGIV) '08 and Multispectral Colour Science (MCS) '08 Final Program and Proceedings (International Science and Technology, 2008), pp. 516-518.
  9. R. J. Woodham, “Reflectance map techniques for analyzing surface defects in metal castings,” Technical Report AI-TR-457 ( MIT, Artificial Intelligence Laboratory, 1987).
  10. R. J. Woodham, “Photometric method for determining surface orientation from multiple images,” Opt. Eng. 19, 139-144(1980).
  11. G. McGunnigle and M. Chantler, “Rough surface description using photometric stereo,” Meas. Sci. Technol. 14, 699-709 (2003). [CrossRef]
  12. K. Ikeuchi, “Determining surface orientations of specular surfaces by using the photometric stereo method,” IEEE Trans. Pattern Anal. Machine Intell. pami-3, 661-669 (1981). [CrossRef]
  13. E. Coleman Jr. and R. Jain, “Obtaining 3-Dimensional shape of textured and specular surfaces using four-source photometry,” Comp. Graph. Image Process. 18, 309-328 (1982). [CrossRef]
  14. S. Barsky and M. Petrou, “The 4-source photometric stereo technique for 3-dimensional surfaces in the presence of highlights and shadows,” IEEE Trans. Pattern Anal. Machine Intell. 25, 1239-1252 (2003). [CrossRef]
  15. H. Tagare and R. de Figuiredo, “A theory of photometric stereo for a class of diffuse non-Lambertian surfaces,” IEEE Trans. Pattern Anal. Machine Intell. 13, 133-152 (1991). [CrossRef]
  16. B. Kim and P. Burguer, “Depth and shape from shading using the photometric stereo method,” Comp. Vis. Graph. Image Process. 54, 416-427 (1991).
  17. M. Oren and S. K. Nayar, “Generalization of Lambert's reflectance model,” Comp. Graph. 28, 239-246 (1994). [CrossRef]
  18. C. Hernández, G. Vogiatzis, and R. Cipolla, “Multiview photometric stereo,” IEEE Trans. Pattern Anal. Machine Intell. 30, 548-554 (2008). [CrossRef]
  19. A. Spence and M. Chantler, “On capturing 3D isotropic surface texture using uncalibrated photometric stereo,” in 3rd International Workshop on Texture Analysis and Synthesis (TextureLab, 2003), pp. 83-88.
  20. M. S. Drew, “Photometric stereo without multiple images,” Proc. SPIE 3016, 369-380 (1997). [CrossRef]
  21. 21. T.-P. Wu, K.-L. Tang, and T.-T. Wong, “Dense photometric stereo: a Markov random field approach,” IEEE Trans. Pattern Anal. Machine Intell. 28, 1830-1846 (2006). [CrossRef]
  22. G. Healey and L. Wang, “Three-dimensional surface segmentation using multicolored illumination,” Opt. Eng. 37, 1553-1562 (1998). [CrossRef]
  23. C. Hernández, G. Vogiatzis, G. J. Brostow, B. Stengar, and R. Cipolla, “Non-rigid photometric stereo with colored lights,” in Proceedings of IEEE International Conference on Computer Vision (IEEE, 2007), pp. 1-8.
  24. M. Chandraker, S. Agarwal, and D. Kriegman, “ShadowCuts: photometric stereo with shadows,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), pp. 1-8.
  25. C. Hernández, Vogiatzis, and R. Cipolla, “Shadows in three-source photometric stereo,” in Proceedings of IEEE European Conference on Computer Vision (IEEE, 2008), pp. 1-14.
  26. K. Schl and O. Witting, “Photometric stereo for non-Lambertian surfaces using color information,” in Proceedings of 5th International Conference on Computer Analysis of Images and Patterns (Springer, 1993), pp. 444-451.
  27. L. L. Kontsevich, A. P. Petrov, and I. S. Vergelskaya, “Reconstruction of shape from shading in color images,” J. Opt. Soc. Am. A 11, 1047-1052 (1994). [CrossRef]
  28. M. S. Drew, “Shape from color,” Technical Report CSS/LCCR TR 92-07 (Simon Fraser University School of Computing Science, 1992).
  29. M. S. Drew, “Optimization approach to dichromatic images,” J. Math. Imaging Vis. 3, 187 (1993). [CrossRef]
  30. P. H. Christensen and L. G. Shapiro “Three dimensional shape from color photometric stereo,” Int. J. Comput. Vis. 13, 213-227 (1994). [CrossRef]
  31. S. Barsky and M. Petrou, “Color photometric stereo: Simultaneous reconstruction of local gradient and color of rough textured surfaces,” in Proceedings of Eighth IEEE International Conference on Computer Vision (IEEE, 2001), pp. 600-605. [CrossRef]
  32. B. Bringier, D. Helbert, and M. Khoudeir, “Photometric reconstruction of a dynamic textured surface from just one color image acquisition,” J. Opt. Soc. Am. 25, 566-574 (2008). [CrossRef]
  33. C.-Yen Chen, R. Klette, and C.-F. Chen, “Recovery of colored surface reflectances using the photometric stereo method,” in Proceedings of International Conference on Information Systems (Association for Information Systems, 2003), pp. 969-974.
  34. M. de Lasarte, J. Pujol, M. Arjona, and M. Vilaseca, “Influence of the size of the training set on color measurements performed using a multispectral imaging system,” in Color in Graphics, Imaging and Vision (CGIV) '08 and Multispectral Colour Science (MCS) '08 Final Program and Proceedings (International Science and Technology, 2008), pp. 437-440.
  35. C. Plata, E. M. Valero, J. L. Nieves, and J. Romero, “Supervised training sample selection for the estimation of spectral reflectance using a RGB camera,” in Color in Graphics, Imaging and Vision (CGIV) '08 and Multispectral Colour Science (MCS) '08 Final Program and Proceedings (International Science and Technology, 2008), pp. 519-522.
  36. Munsell Book of Color--Matte Finish Collection (Munsell Color, 1976).
  37. Corbalan, Millan, and Yzuel, “Color measurement in standard CIELab coordinates using a 3CCD camera: correction for the influence of the light source,” Opt. Eng. 39, 1470-1476(2000). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited