A Color Adjustment Method for Automatic Seamless Image Blending

  • Xianji Li
  • Dongho Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4551)


In this paper we present a stable automatic system for image composition, which can well control the color difference between two images, and produce a seamless composite image with color continuity. This is a user-friendly system that reduces the user’s manual tasks. We observe that Poisson image editing written by Perez et al. [8] blends well for seamless boundary automatically. However, the color of user-selected region can be changed after applying this method. So the object loses its original color tone after blending. To solve this problem, firstly we check out the case of object color being changed rapidly. It can be done by calculating color temperatures of two input images and comparing the white balance with each other. Next, a distance ratio rule is applied to controls the pixels included in the region between the user-selected boundary and object boundary.


image composition Poisson Image Editing object color color temperatures distance ratio rule 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Berman, A., Vlahos, P., Dadourian, A.: Comprehensive method for removing from an image the background surrounding a selected object. U.S. Patent 6, 134, 345 Google Scholar
  2. 2.
    Burt, P.J., Adelson.: Multiresolution spline with application to image mosaics. ACM Transactions on Graphics 2, 217–236 (1983)CrossRefGoogle Scholar
  3. 3.
    Ballester, C., Bertalmio, M., Caselles, V.: Filling-In by Joint Interpolation of Vector Fields and Gray Levels. IEEE Transactions on Image Processing 10(8) (August 2001)Google Scholar
  4. 4.
    Jia, J., Tian, S., C.-K., H.-Y.: Drag-and-Drop Pasting. In: ACM SIGGRAPH conference proceedings (2006) Google Scholar
  5. 5.
    Jia, J., Tang, -K.: Eliminating structure and intensity misalignment in image stitching. In: Proceedings of ICCV (2005) Google Scholar
  6. 6.
    Levin, A., Zomet, A., Peleg, S., Weiss, Y.: Seamless image stitching in the gradient domain. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 377–389. Springer, Heidelberg (2004)Google Scholar
  7. 7.
    Li, Y., Sun, J., Tang, C., Shum, H.: Lazy Snapping. ACM Transaction on Graphics vol 23(3) (Apri 2004) Google Scholar
  8. 8.
    Perez, P., Gangnet, M., Blake, A.: Poisson image editing. In: Proceedings of ACM SIGGRAPH, pp. 313–318 (2003) Google Scholar
  9. 9.
    Rother, C., Kolmogorov, V., Blake, A.: grabcut - interactive foreground extraction using iterated graph cut. In: Proceedings of ACM SIGGRAPH, pp. 309–314 (2004) Google Scholar
  10. 10.
    Ruzon, M., Tomasi, C.: Alpha estimation in natural images. In: Proceedings of CVPR 2000 (2000) Google Scholar
  11. 11.
    Sun, J., Jia. J., Tang, C., Shum, H.: Poisson matting. In: Proceedings of ACM SIGGRAPH, pp. 315–321 (2004)Google Scholar
  12. 12.
    Wyszecki, G., Stiles, W.S.: Color Science: Concepts and Methods, Quantitative Data and Formulae. John Wiley & Sons, Inc, Chichester (1982)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Xianji Li
    • 1
  • Dongho Kim
    • 1
  1. 1.Department of Digital Media, Graduate School of Soongsil University, 511 Sangdo-dong, Dongjak-gu, SeoulKorea

Personalised recommendations