Skip to main content
Log in

Consistent color and detail transfer from multiple source images for video and images

  • Original Article
  • Published:
The Visual Computer Aims and scope Submit manuscript


In this paper, we propose a method to jointly transfer the color and detail of multiple source images to a target video or image. Our method is based on a probabilistic segmentation scheme using Gaussian mixture model (GMM) to divide each source image as well as the target video frames or image into soft regions and determine the relevant source regions for each target region. For detail transfer, we first decompose each image as well as the target video frames or image into base and detail components. Then histogram matching is performed for detail components to transfer the detail of matching regions from source images to the target. We propose a unified framework to perform both color and detail transforms in an integrated manner. We also propose a method to maintain consistency for video targets, by enforcing consistent region segmentations for consecutive video frames using GMM-based parameter propagation and adaptive scene change detection. Experimental results demonstrate that our method automatically produces consistent color and detail transferred videos and images from a set of source images.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others


  1. Bae, S., Paris, S., Durand, F.: Two-scale tone management for photographic look. In: Proceedings of SIGGRAPH (2006)

  2. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(24), 509–522 (2002)

    Article  Google Scholar 

  3. Brown, M., Lowe, D.G.: Automatic panoramic image stitching using invariant features. Int. J. Comput. Vis. 74(1), 59–73 (2007)

    Article  Google Scholar 

  4. Demetriou, M., Hardeberg, J., Adelmann, G.: Computer-aided reclamation of lost art. In: Proceedings of European Conference on Computer Vision 2012 Workshops and Demonstrations (2012)

  5. Fecker, U., Barkowsky, M., Kaup, A.: Histogram-based prefiltering for luminance and chrominance compensation of multiview video. IEEE Trans. Circuits Syst. Video Technol. 18(9), 1258–1267 (2008)

    Article  Google Scholar 

  6. Galasso, F., Nagaraja, N., Cardenas, T., Brox, T., Schiele, B.: A unified video segmentation benchmark: annotation, metrics and analysis. In: Proceedings of IEEE International Conference on Computer Vision (2013)

  7. Gonzalez, R., Woods, R.: Digital Image Processing, 2nd edn. Prenticel Hall, Upper Saddle River

  8. Gould, S., Rodgers, J., Cohen, D., Elidan, G., Koller, D.: Multi-class segmentation with relative location prior. Int. J. Comput. Vis. 80(1), 300–316 (2008)

    Article  Google Scholar 

  9. Hertzmann, A., Jacobs, C., Oliver, N., Curless, B., Salesin, D.: Image analogies. In: Proceedings of SIGGRAPH (2001)

  10. Huang, H., Zang, Y., Li, C.F.: Example-based painting guided by color features. Vis. Comput. 26(6), 933–942 (2010)

    Article  Google Scholar 

  11. Hwang, Y., Lee, J.Y., Kweon, I.S., Kim, S.J.: Color transfer using probabilistic moving least squares. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2014)

  12. Jia, J., Tang, C.K.: Tensor voting for image correction by global and local intensity alignment. IEEE Trans. Pattern Anal. Mach. Intell. 27(1), 36–50 (2005)

    Article  Google Scholar 

  13. Kim, S.J., Pollefeys, M.: Robust radiometric calibration and vignetting correction. IEEE Trans. Pattern Anal. Mach. Intell. 30(4), 562–576 (2008)

    Article  Google Scholar 

  14. Li, B., Jiang, G., Shao, W.: Color correction based on point clouds alignment in the logarithmic rgb space. Vis. Comput. 31(3), 257–270 (2015)

    Article  Google Scholar 

  15. Li, K., Dai, Q., Xu, W.: Color transfer based on wavelet transform. In: Proceedings of Visual Communications and Image Processing (VCIP) (2008)

  16. Musialski, P., Cui, M., Ye, J., Razdan, A., Wonka, P.: A framework for interactive image color editing. Vis. Comput. 29(11), 1173–1186 (2013)

    Article  Google Scholar 

  17. Nguyen, B.P., Tay, W.L., Chui, C.K., Ong, S.H.: A clustering-based system to automate transfer function design for medical image visualization. Vis. Comput. 28(2), 181–191 (2012)

    Article  Google Scholar 

  18. Pitit, F., Kokaram, A.C., Dahyot, R.: Automated colour grading using colour distribution transfer. Comput. Vis. Image Underst. 107(1), 123–137 (2007)

    Article  Google Scholar 

  19. Reinhard, E., Ashikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Comput. Graph. Appl. 21(5), 34–41 (2001)

    Article  Google Scholar 

  20. Shih, Y., Paris, S., Barnes, C., Freeman, W., Durand, F.: Style transfer for headshot portraits. In: Proceedings of SIGGRAPH (2014)

  21. Su, Z., Luo, X., Artusi, A.: A novel image decomposition approach and its applications. Vis. Comput. 29(10), 1011–1023 (2013)

    Article  Google Scholar 

  22. Tai, Y.W., Jia, J., Tang, C.K.: Soft color segmentation and its applications. IEEE Trans. Pattern Anal. Mach. Intell. 29(9), 1520–1537 (2007)

    Article  Google Scholar 

  23. Xiang, Y., Zou, B., Li, H.: Selective color transfer with multi-source images. Pattern Recognit. Lett. 30(1), 682–689 (2009)

  24. Xiao, X., Ma, L.: Color transfer in correlated color space. In: Proceedings of ACM International Conference on Virtual Reality Continuum and Its Applications (2006)

  25. Xu, W., Mulligan, J.: Performance evaluation of color correction approaches for automatic multi-view image and video stitching. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2010)

  26. Yang, Q., Tan, K.H., Ahuja, N.: Real-time o(1) bilateral filtering. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2009)

  27. Zang, Y., Huang, H., Li, C.F.: Artistic preprocessing for painterly rendering and image stylization. Vis. Comput. 30(9), 969–979 (2014)

    Article  Google Scholar 

  28. Zhang, M., Georganas, N.D.: Fast color correction using principal regions mapping in different color spaces. Real-Time Imaging 10(1), 23–30 (2004)

    Article  Google Scholar 

Download references


This work was partially supported by the new faculty research fund of Ajou University, and partially supported by Hankuk University of Foreign Studies Research Fund of 2015, and also partially supported by the Soonchunhyang university research fund.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Ho Yub Jung.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Heo, Y.S., Lee, S. & Jung, H.Y. Consistent color and detail transfer from multiple source images for video and images. Vis Comput 32, 1273–1289 (2016).

Download citation

  • Published:

  • Issue Date:

  • DOI: