Real-Time Specular Highlight Removal Using Bilateral Filtering

  • Qingxiong Yang
  • Shengnan Wang
  • Narendra Ahuja
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6314)


In this paper, we propose a simple but effective specular highlight removal method using a single input image. Our method is based on a key observation - the maximum fraction of the diffuse color component (so called maximum diffuse chromaticity in the literature) in local patches in color images changes smoothly. Using this property, we can estimate the maximum diffuse chromaticity values of the specular pixels by directly applying low-pass filter to the maximum fraction of the color components of the original image, such that the maximum diffuse chromaticity values can be propagated from the diffuse pixels to the specular pixels. The diffuse color at each pixel can then be computed as a nonlinear function of the estimated maximum diffuse chromaticity. Our method can be directly extended for multi-color surfaces if edge-preserving filters (e.g., bilateral filter) are used such that the smoothing can be guided by the maximum diffuse chromaticity. But maximum diffuse chromaticity is to be estimated. We thus present an approximation and demonstrate its effectiveness. Recent development in fast bilateral filtering techniques enables our method to run over 200× faster than the state-of-the-art on a standard CPU and differentiates our method from previous work.


  1. 1.
    Bajcsy, R., Lee, S., Leonardis, A.: Detection of diffuse and specular interface reflections and inter-reflections by color image segmentation. IJCV 17(3), 241–272 (1996)CrossRefGoogle Scholar
  2. 2.
    Durand, F., Dorsey, J.: Fast bilateral filtering for the display of high-dynamic-range images. In: Siggraph, vol. 21 (2002)Google Scholar
  3. 3.
    Klinker, G., Shafer, S., Kanade, T.: The measurement of highlights in color images. IJCV 2(1), 7–32 (1988)CrossRefGoogle Scholar
  4. 4.
    Lee, S., Bajcsy, R.: Detection of specularity using color and multiple views. In: Sandini, G. (ed.) ECCV 1992. LNCS, vol. 588, pp. 99–114. Springer, Heidelberg (1992)Google Scholar
  5. 5.
    Lin, S., Li, Y., Kang, S., Tong, X., Shum, H.Y.: Diffuse-specular separation and depth recovery from image sequences. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2352, pp. 210–224. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Lin, S., Shum, H.Y.: Separation of diffuse and specular reflection in color images. In: CVPR, pp. 341–346 (2001)Google Scholar
  7. 7.
    Mallick, S.P., Zickler, T., Belhumeur, P.N., Kriegman, D.J.: Specularity removal in images and videos: A pde approach. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 550–563. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Mallick, S.P., Zickler, T.E., Kriegman, D.J., Belhumeur, P.N.: Beyond lambert: Reconstructing specular surfaces using color. In: CVPR, pp. II619–II626 (2005)Google Scholar
  9. 9.
    Nayar, S., Fang, X., Boult, T.: Separation of reflection components using color and polarization. IJCV 21(3) (1996)Google Scholar
  10. 10.
    Paris, S., Durand, F.: A fast approximation of the bilateral filter using a signal processing approach. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954, pp. 568–580. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Park, J., Tou, J.: Highlight separation and surface orientation for 3-d specular objects. In: ICPR, pp. I331–I335 (1990)Google Scholar
  12. 12.
    Porikli, F.: Constant time o(1) bilateral filtering. In: CVPR (2008)Google Scholar
  13. 13.
    Sato, Y., Ikeuchi, K.: Temporal-color space analysis of reflection. JOSA 11(11), 2990–3002 (1994)CrossRefGoogle Scholar
  14. 14.
    Shafer, S.: Using color to separate reflection components. Color Res. App. 10(4), 210–218 (1985)CrossRefGoogle Scholar
  15. 15.
    Shen, H.L., Cai, Q.Y.: Simple and efficient method for specularity removal in an image. Applied Optics 48(14), 2711–2719 (2009)CrossRefMathSciNetGoogle Scholar
  16. 16.
    Tan, P., Lin, S., Quan, L., Shum, H.Y.: Highlight removal by illumination-constrained inpainting. In: ICCV, p. 164 (2003)Google Scholar
  17. 17.
    Tan, P., Quan, L., Lin, S.: Separation of highlight reflections on textured surfaces. In: CVPR, pp. 1855–1860 (2006)Google Scholar
  18. 18.
    Tan, R.: Highlight removal from a single image,
  19. 19.
    Tan, R., Ikeuchi, K.: Reflection components decomposition of textured surfaces using linear basis functions. In: CVPR, pp. I125–I131 (2005)Google Scholar
  20. 20.
    Tan, R., Ikeuchi, K.: Separating reflection components of textured surfaces using a single image. PAMI 27(2), 178–193 (2005)Google Scholar
  21. 21.
    Tan, R.T., Nishino, K., Ikeuchi, K.: Illumination chromaticity estimation using inverse-intensity chromaticity space. In: CVPR, pp. 673–680 (2003)Google Scholar
  22. 22.
    Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: ICCV, pp. 839–846 (1998)Google Scholar
  23. 23.
    Yang, Q., Tan, K.H., Ahuja, N.: Real-time o(1) bilateral filtering. In: CVPR (2009)Google Scholar
  24. 24.
    Yang, Q., Wang, S., Ahuja, N.: SVM for Edge-Preserving Filtering. In: CVPR (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Qingxiong Yang
    • 1
  • Shengnan Wang
    • 1
  • Narendra Ahuja
    • 1
  1. 1.University of Illinos, Urbana Champaign 

Personalised recommendations