A New Shadow Removal Method Using Color-Lines

  • Xiaoming Yu
  • Ge LiEmail author
  • Zhenqiang Ying
  • Xiaoqiang Guo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10425)


In this paper, we present a novel method for single-image shadow removal. From the observation of images with shadow, we find that the pixels from the object with same material will form a line in the RGB color space as illumination changes. Besides, we find these lines do not cross with the origin due to the effect of ambient light. Thus, we establish an offset correction relationship to remove the effect of ambient light. Then we derive a linear shadow image model to perform color-line identification. With the linear model, our shadow removal method is proposed as following. First, perform color-line clustering and illumination estimation. Second, use an on-the-fly learning method to detect umbra and penumbra. Third, estimate the shadow scale by the statistics of shadow-free regions. Finally, refine the shadow scale by illumination optimization. Our method is simple and effective for producing high-quality shadow-free images and has the ability for processing scenes with rich texture types and non-uniform shadows.


Shadow removal Enhancement Color line Offset correction 



This work was supported by the grant of National Science Foundation of China (No. U1611461), Shenzhen Peacock Plan (20130408-183003656), Guangdong Province Projects (2014B010117007), and Science and Technology Planning Project of Guangdong Province, China (No. 2014B090910001).


  1. 1.
    Arbel, E., Hel-Or, H.: Shadow removal using intensity surfaces and texture anchor points. IEEE Trans. Pattern Anal. Mach. Intell. 33(6), 1202–1216 (2011)CrossRefGoogle Scholar
  2. 2.
    Barrow, H., Tenenbaum, J.: Recovering intrinsic scene characteristics from images. In: Hanson, A., Risenman, E. (eds.) Computer Vision Systems (1978)Google Scholar
  3. 3.
    Berman, D., Avidan, S., et al.: Non-local image dehazing. In: Computer Vision and Pattern Recognition, pp. 1674–1682. IEEE (2016)Google Scholar
  4. 4.
    Finlayson, G.D., Hordley, S.D., Drew, M.S.: Removing shadows from images. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 823–836. Springer, Heidelberg (2002). doi: 10.1007/3-540-47979-1_55 CrossRefGoogle Scholar
  5. 5.
    Finlayson, G.D., Hordley, S.D., Lu, C., Drew, M.S.: On the removal of shadows from images. IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 59–68 (2006)CrossRefGoogle Scholar
  6. 6.
    Gong, H., Cosker, D.: Shadow removal dataset and online benchmark for variable scene categories.
  7. 7.
    Gong, H., Cosker, D.: Interactive removal and ground truth for difficult shadow scenes. JOSA A 33(9), 1798–1811 (2016)CrossRefGoogle Scholar
  8. 8.
    Guo, R., Dai, Q., Hoiem, D.: Paired regions for shadow detection and removal. IEEE Trans. Pattern Anal. Mach. Intell. 35(12), 2956–2967 (2013)CrossRefGoogle Scholar
  9. 9.
    Huang, J.B., Chen, C.S.: Moving cast shadow detection using physics-based features. In: Computer Vision and Pattern Recognition, pp. 2310–2317. IEEE (2009)Google Scholar
  10. 10.
    Khan, S.H., Bennamoun, M., Sohel, F., Togneri, R.: Automatic shadow detection and removal from a single image. IEEE Trans. Pattern Anal. Mach. Intell. 38(3), 431–446 (2016)CrossRefGoogle Scholar
  11. 11.
    Maxwell, B.A., Friedhoff, R.M., Smith, C.A.: A bi-illuminant dichromatic reflection model for understanding images. In: Computer Vision and Pattern Recognition, pp. 1–8. IEEE (2008)Google Scholar
  12. 12.
    Mohan, A., Tumblin, J., Choudhury, P.: Editing soft shadows in a digital photograph. IEEE Comput. Graph. Appl. 27(2), 23–31 (2007)CrossRefGoogle Scholar
  13. 13.
    Omer, I., Werman, M.: Color lines: Image specific color representation. In: Computer Vision and Pattern Recognition, vol. 2, p. II. IEEE (2004)Google Scholar
  14. 14.
    Prati, A., Mikic, I., Trivedi, M.M., Cucchiara, R.: Detecting moving shadows: algorithms and evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 25(7), 918–923 (2003)CrossRefGoogle Scholar
  15. 15.
    Reinhard, E., Adhikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Comput. Graph. Appl. 21(5), 34–41 (2001)CrossRefGoogle Scholar
  16. 16.
    Shor, Y., Lischinski, D.: The shadow meets the mask: pyramid-based shadow removal. In: Computer Graphics Forum, vol. 27, pp. 577–586 (2008)Google Scholar
  17. 17.
    Wu, T.P., Tang, C.K.: A Bayesian approach for shadow extraction from a single image. In: Computer Vision-ICCV, vol. 1, pp. 480–487. IEEE (2005)Google Scholar
  18. 18.
    Wu, T.P., Tang, C.K., Brown, M.S., Shum, H.Y.: Natural shadow matting. ACM Trans. Graph. 26(2), 8 (2007)CrossRefGoogle Scholar
  19. 19.
    Xiao, C., She, R., Xiao, D., Ma, K.L.: Fast shadow removal using adaptive multi-scale illumination transfer. Computer Graphics Forum, vol. 32, pp. 207–218 (2013)Google Scholar
  20. 20.
    Xu, L., Qi, F., Jiang, R.: Shadow removal from a single image. In: Intelligent Systems Design and Applications, vol. 2, pp. 1049–1054. IEEE (2006)Google Scholar
  21. 21.
    Ying, Z., Li, G.: Robust lane marking detection using boundary-based inverse perspective mapping. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1921–1925. IEEE (2016)Google Scholar
  22. 22.
    Ying, Z., Li, G., Tan, G.: An illumination-robust approach for feature-based road detection. In: 2015 IEEE International Symposium on Multimedia (ISM), pp. 278–281. IEEE (2015)Google Scholar
  23. 23.
    Ying, Z., Li, G., Wen, S., Tan, G.: ORGB: Offset correction in RGB color space for illumination-robust image processing. In: International Conference on Acoustics, Speech and Signal Processing. IEEE (2017, in press)Google Scholar
  24. 24.
    Ying, Z., Li, G., Zang, X., Wang, R., Wang, W.: A novel shadow-free feature extractor for real-time road detection. In: Proceedings of the 2016 ACM on Multimedia Conference, pp. 611–615. ACM (2016)Google Scholar
  25. 25.
    Zhang, L., Zhang, Q., Xiao, C.: Shadow remover: image shadow removal based on illumination recovering optimization. IEEE Trans. Image Process. 24(11), 4623–4636 (2015)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Xiaoming Yu
    • 1
    • 2
  • Ge Li
    • 1
    Email author
  • Zhenqiang Ying
    • 1
  • Xiaoqiang Guo
    • 3
  1. 1.School of Electronic and Computer Engineering, Shenzhen Graduate SchoolPeking UniversityShenzhenChina
  2. 2.Computer Science and TechnologyDalian University of TechnologyDalianChina
  3. 3.Academy of Broadcasting Science, SAPPRFTPekingChina

Personalised recommendations