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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 8, Iss. 8 — Sep. 4, 2013

Real-time highlight removal using intensity ratio

Hui-Liang Shen and Zhi-Huan Zheng  »View Author Affiliations


Applied Optics, Vol. 52, Issue 19, pp. 4483-4493 (2013)
http://dx.doi.org/10.1364/AO.52.004483


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Abstract

In this paper, we propose an efficient method to separate the diffuse and specular reflection components from a single image. The method is built on the observation that, for diffuse pixels, the intensity ratios between the maximum values and range values (maximums minus minimums) are independent of surface geometry. The specular fractions of the image pixels can then be computed by using the intensity ratio. For textured surfaces, image pixels are classified into clusters by constructing a pseudo-chromaticity space, and the intensity ratio of each cluster is robustly estimated. Unlike existing techniques, the proposed method works in a pixel-wise manner, without specular pixel identification and any local interaction. Experimental results show that the proposed method runs 4× faster than the state of the art and produces improved accuracy in specular highlight removal.

© 2013 Optical Society of America

OCIS Codes
(120.5700) Instrumentation, measurement, and metrology : Reflection
(330.1690) Vision, color, and visual optics : Color
(150.1135) Machine vision : Algorithms

ToC Category:
Machine Vision

History
Original Manuscript: March 28, 2013
Revised Manuscript: May 23, 2013
Manuscript Accepted: May 24, 2013
Published: June 24, 2013

Virtual Issues
Vol. 8, Iss. 8 Virtual Journal for Biomedical Optics

Citation
Hui-Liang Shen and Zhi-Huan Zheng, "Real-time highlight removal using intensity ratio," Appl. Opt. 52, 4483-4493 (2013)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-52-19-4483


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References

  1. T. Gevers and H. Stokman, “Classifying color edges in video into shadow-geometry, highlight, or material transitions,” IEEE Trans. Multimedia 5, 237–243 (2003).
  2. R. T. Tan, K. Nishino, and K. Ikeuchi, “Color constancy through inverse-intensity chromaticity space,” J. Opt. Soc. Am. A 21, 321–334 (2004). [CrossRef]
  3. J. Toro and B. Funt, “A multilinear constraint on dichromatic planes for illumination estimation,” IEEE Trans. Image Process. 16, 92–97 (2007). [CrossRef]
  4. Q. Yang, S. Wang, N. Ahuja, and R. Yang, “A uniform framework for estimating illumination chromaticity, correspondence and specular reflection,” IEEE Trans. Image Process. 20, 53–63 (2011). [CrossRef]
  5. S. P. Mallick, T. E. Zickler, D. J. Kriegman, and P. N. Belhumeur, “Beyond Lambert: reconstructing specular surfaces using color,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005 (IEEE Computer Society, 2005), Vol. 2, pp. 619–626.
  6. D. Miyazaki, K. Hara, and K. Ikeuchi, “Median photometric stereo as applied to the Segonko tumulus,” Int. J. Comput. Vis. 86, 229–242 (2010). [CrossRef]
  7. H. C. Lee, D. J. Breneman, and C. O. Schulte, “Modeling light reflection for computer color vision,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 402–409 (1990). [CrossRef]
  8. A. Artusi, F. Banterle, and D. Chetverikov, “A survey of specularity removal methods,” Comput. Graph. Forum 30, 2208–2230 (2011). [CrossRef]
  9. G. J. Klinker, S. A. Shafer, and T. Kanade, “The measurement of highlights in color images,” Int. J. Comput. Vis. 2, 7–32 (1988). [CrossRef]
  10. Y. Sato and K. Ikeuchi, “Temporal-color space analysis of reflection,” J. Opt. Soc. Am. A 11, 2990–3002 (1994). [CrossRef]
  11. R. T. Tan, K. Nishino, and K. Ikeuchi, “Separating reflection components based on chromaticity and noise analysis,” IEEE Trans. Pattern Anal. Mach. Intell. 26, 1373–1379 (2004). [CrossRef]
  12. R. T. Tan and K. Ikeuchi, “Separating reflection components of textured surfaces using a single image,” IEEE Trans. Pattern Anal. Mach. Intell. 27, 178–193 (2005). [CrossRef]
  13. R. T. Tan and K. Ikeuchi, “Reflection components decomposition of texured surfaces using linear basis functions,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005 (IEEE Computer Society, 2005), Vol. 1, pp. 125–131.
  14. S. K. Nayar, X. S. Fang, and T. Boult, “Separation of reflection components using color and polarization,” Int. J. Comput. Vis. 21, 163–186 (1997). [CrossRef]
  15. S. Lin, Y. Li, S. B. Kang, X. Tong, and H.-Y. Shum, “Diffuse-specular separation and depth recovery from image sequences,” in Computer Vision—ECCV 2002 (Springer, 2002), pp. 210–224.
  16. P. Tan, S. Lin, L. Quan, and H. Y. Shum, “Highlight removal by illumination-constrained inpainting,” in Ninth IEEE International Conference on Computer Vision (IEEE, 2003), Vol. 1, pp. 164–169.
  17. S. P. Mallick, T. E. Zickler, P. N. Belhumeur, and D. J. Kriegman, “Specularity removal in images and videos: a PDE approach,” in Computer Vision—ECCV 2006 (Springer, 2006), Vol. 1, pp. 550–563.
  18. H. L. Shen, H. G. Zhang, S. J. Shao, and J. H. Xin, “Chromaticity-based separation of reflection components in a single image,” Pattern Recogn. 41, 2461–2469 (2008). [CrossRef]
  19. Q. Yang, S. Wang, and N. Ahuja, “Real-time specular highlight removal using bilateral filtering,” in Computer Vision–ECCV 2010 (Springer, 2010), pp. 87–100.
  20. H. L. Shen and Q. Y. Cai, “Simple and efficient method for specularity removal in an image,” Appl. Opt. 48, 2711–2719 (2009). [CrossRef]
  21. S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10, 210–218 (1985). [CrossRef]
  22. S. Barsky and M. Petrou, “The 4-source photometric stereo technique for three-dimensional surfaces in the presence of highlights and shadows,” IEEE Trans. Pattern Anal. Mach. Intell. 25, 1239–1252 (2003). [CrossRef]
  23. J. van de Weijer and T. Gevers, “Edge-based color constancy,” IEEE Trans. Image Process. 16, 2207–2214 (2007). [CrossRef]
  24. K. J. Yoon and I. S. Kweon, “Voting-based separation of diffuse and specular pixels,” Electron. Lett. 40, 1260–1261 (2004). [CrossRef]
  25. D. Xu, C. Doutre, and P. Nasiopoulos, “Correction of clipped pixels in color images,” IEEE Trans. Vis. Comput. Graph. 17, 333–344 (2011).
  26. R. T. Tan, “Specular highlight removal from a single image,” http://people.cs.uu.nl/robby/code.html .
  27. Q. Yang, “Real-time specular highlight removal using bilateral filtering,” http://www.cs.cityu.edu.hk/~qiyang/ .

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