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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 48, Iss. 14 — May. 10, 2009
  • pp: 2711–2719

Simple and efficient method for specularity removal in an image

Hui-Liang Shen and Qing-Yuan Cai  »View Author Affiliations


Applied Optics, Vol. 48, Issue 14, pp. 2711-2719 (2009)
http://dx.doi.org/10.1364/AO.48.002711


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Abstract

For dielectric inhomogeneous objects, the perceived reflections are the linear combinations of diffuse and specular reflection components. Specular reflection plays an important role in the fields of image analysis, pattern recognition, and scene synthesis. Several methods for the separation of the diffuse and the specular reflection components have been presented based on image segmentation or local interaction of neighboring pixels. We propose a simple and effective method for specularity removal in a single image on the level of each individual pixel. The chromaticity of diffuse reflection is approximately estimated by employing the concept of modified specular-free image, and the specular component is adjusted according to the criterion of smooth color transition along the boundary of diffuse and specular regions. Experimental results indicate that the proposed method is promising when compared with other state-of-the-art techniques, in both separation accuracy and running speed.

© 2009 Optical Society of America

OCIS Codes
(100.2960) Image processing : Image analysis
(100.3020) Image processing : Image reconstruction-restoration
(330.1690) Vision, color, and visual optics : Color

ToC Category:
Image Processing

History
Original Manuscript: September 23, 2008
Revised Manuscript: March 27, 2009
Manuscript Accepted: April 9, 2009
Published: May 6, 2009

Virtual Issues
Vol. 4, Iss. 7 Virtual Journal for Biomedical Optics

Citation
Hui-Liang Shen and Qing-Yuan Cai, "Simple and efficient method for specularity removal in an image," Appl. Opt. 48, 2711-2719 (2009)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-48-14-2711


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References

  1. S. Lin and S. W. Lee, “Estimation of diffuse and specular appearance,” in International Conference on Computer Vision (ICCV) (IEEE, 1999), pp. 855-860.
  2. K. Hara, K. Nishino, and K. Ikeuchi, “Determining reflectance and light position from a single image without distant illumination assumption,” in International Conference on Computer Vision (ICCV) (IEEE, 2003), Vol. 1, pp. 560-567. [CrossRef]
  3. J. H. Xin and H. L. Shen, “Accurate color synthesis of three-dimensional objects in an image,” J. Opt. Soc. Am. A 21, 713-723 (2004). [CrossRef]
  4. S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10, 210-218 (1985). [CrossRef]
  5. 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]
  6. 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]
  7. 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]
  8. 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] [PubMed]
  9. D. Miyazaki, R. T. Tan, K. Hara, and K. Ikeuchi, “Polarization-based inverse rendering from a single view,” in International Conference on Computer Vision (ICCV) (IEEE, 2003), Vol. 2, pp. 982-987. [CrossRef]
  10. K. J. Yoon, Y. J. Choi, and I. S. Kweon, “Fast separation of reflection components using a specularity-invariant image representation,” in International Conference on Image Processing (ICIP) (IEEE, 2006), pp. 973-976.
  11. H. L. Shen, H. G. Zhang, S. J. Shao, and J. H. Xin, “Chromaticity-based separation of reflection components in a single image,” Pattern Recognit. 41, 2461-2469 (2008). [CrossRef]
  12. L. Shen, T. Machida, and H. Takemura, “Efficient photometric stereo technique for three-dimensional surfaces with unknown BRDF,” in the Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05) (IEEE, 2005), pp. 326-333. [CrossRef]
  13. 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]
  14. R. T. Tan and K. Ikeuchi, “Reflection components decomposition of textured surface using linear basis functions,” in Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE, 2005), Vol. 1, pp. 125-131.
  15. S. P. Mallick, T. Zickler, P. N. Belhumeur, and D. J. Kriegman, “Specularity removal in images and videos: a PDE approach,” in 9th European Conference on Computer Vision, ECCV 2006, A. Leonardis, H. Bischof, and A. Pinz, eds., Vol. 3951 of Lecture Notes in Computer Science (Springer, 2006), pp. 550-563. [CrossRef]
  16. S. Mallick, T. Zickler, D. Kriegman, and P. Belhumeur, “Beyond Lambert: reconstructing specular surfaces using color,” in Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE, 2005) Vol. 2, pp. 619-626.
  17. J. W. Park and K. H. Lee, “Inpainting highlights using color line projection,” IEICE Trans. Inf. Syst. E90D, 250-257(2007). [CrossRef]
  18. P. Tan, S. Lin, L. Quan, and H. Y. Shum, “Highlight removal by illumination constrained inpainting,” in International Conference on Computer Vision (ICCV) (IEEE, 2003), pp. 164-169.
  19. K. Barnard, V. Cardei, and B. Funt, “A comparison of computational color constancy algorithms. I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972-984 (2002). [CrossRef]

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