Interactive local adjustment of tonal values

Abstract

This paper presents a new interactive tool for making local adjustments of tonal values and other visual parameters in an image. Rather than carefully selecting regions or hand-painting layer masks, the user quickly indicates regions of interest by drawing a few simple brush strokes and then uses sliders to adjust the brightness, contrast, and other parameters in these regions. The effects of the user's sparse set of constraints are interpolated to the entire image using an edge-preserving energy minimization method designed to prevent the propagation of tonal adjustments to regions of significantly different luminance. The resulting system is suitable for adjusting ordinary and high dynamic range images, and provides the user with much more creative control than existing tone mapping algorithms. Our tool is also able to produce a tone mapping automatically, which may serve as a basis for further local adjustments, if so desired. The constraint propagation approach developed in this paper is a general one, and may also be used to interactively control a variety of other adjustments commonly performed in the digital darkroom.

References

1. Adams, A. 1981. The Negative. The Ansel Adams Photography series. Little, Brown and Company.
2. Adams, A. 1983. The Print. The Ansel Adams Photography series. Little, Brown and Company.
3. Adobe Systems, Inc. 2005. Adobe Photoshop CS2. Adobe Systems, Inc., San Jose, CA.
4. Agarwala, A., Dontcheva, M., Agrawala, M., Drucker, S., Colburn, A., Curless, B., Salesin, D., and Cohen, M. 2004. Interactive digital photomontage. ACM Trans. Graph. 23, 3, 294--302.
5. Artusi, A., Bittner, J., Wimmer, M., and Wilkie, A. 2003. Delivering interactivity to complex tone mapping operators. In Rendering Techniques 2003, 38--44.
6. Ashikhmin, M. 2002. A tone mapping algorithm for high contrast images. In Rendering Techniques 2002, 145--156.
7. Drago, F., Myszkowski, K., Annen, T., and Chiba, N. 2003. Adaptive logarithmic mapping for displaying high contrast scenes. Computer Graphics Forum 22, 3 (Sept.), 419--426.
8. Durand, F., and Dorsey, J. 2000. Interactive tone mapping. In Rendering Techniques 2000, 219--230.
9. Durand, F., and Dorsey, J. 2002. Fast bilateral filtering for the display of high-dynamic-range images. ACM Trans. Graph. 21, 3 (July), 257--266.
10. Fattal, R., Lischinski, D., and Werman, M. 2002. Gradient domain high dynamic range compression. ACM Trans. Graph. 21, 3 (July), 249--256.
11. Goodnight, N., Wang, R., Woolley, C., and Humphreys, G. 2003. Interactive time-dependent tone mapping using programmable graphics hardware. In Rendering Techniques 2003, 26--37.
12. Johnson, G. M., and Fairchild, M. D. 2003. Rendering HDR images. In IS&T/SID 11th Color Imaging Conference, 36--41.
13. Levin, A., Lischinski, D., and Weiss, Y. 2004. Colorization using optimization. ACM Trans. Graph. 23, 3, 689--694.
14. Li, Y., Sun, J., Tang, C.-K., and Shum, H.-Y. 2004. Lazy snapping. ACM Trans. Graph. 23, 3, 303--308.
15. Li, Y., Sharan, L., and Adelson, E. H. 2005. Compressing and companding high dynamic range images with subband architectures. ACM Trans. Graph. 24, 3, 836--844.
16. Pattanaik, S. N., Ferwerda, J. A., Fairchild, M. D., and Green-Berg, D. P. 1998. A multiscale model of adaptation and spatial vision for realistic image display. In Proc. ACM SIGGRAPH 98, M. Cohen, Ed., 287--298.
17. Reichmann, M., 2005. An image processing workflow. http://luminous-landscape.com/tutorials/workflow1.shtml.
18. Reinhard, E., Stark, M., Shirley, P., and Ferwerda, J. 2002. Photographic tone reproduction for digital images. ACM Trans. Graph. 21, 3 (July), 267--276.
19. Reinhard, E., Ward, G., Pattanaik, S., and Debevec, P. 2005. High Dynamic Range Imaging. Morgan Kaufmann.
20. Reinhard, E. 2002. Parameter estimation for photographic tone reproduction. Journal of Graphics Tools 7, 1, 45--52.
21. Rother, C., Kolmogorov, V., and Blake, A. 2004. "GrabCut": interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23, 3, 309--314.
22. Saad, Y. 2003. Iterative Methods for Sparse Linear Systems, second ed. SIAM.
23. Szeliski, R. 2006. Locally adapted hierarchical basis preconditioning. ACM Trans. Graph. 25, 3.
24. Tumblin, J., and Turk, G. 1999. LCIS: A boundary hierarchy for detail-preserving contrast reduction. In Proc. ACM SIGGRAPH 99, A. Rock-wood, Ed., 83--90.
25. Wang, J., and Cohen, M. 2005. An iterative optimization approach for unified image segmentation and matting. In Proc. IEEE Intl. Conf. on Computer Vision, vol. 2, 930--935.
26. Ward Larson, G., Rushmeier, H., and Piatko, C. 1997. A visibility matching tone reproduction operator for high dynamic range scenes. IEEE TVCG 3, 4, 291--306.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Computer vision tasks

  • Computer graphics

    • Graphics systems and interfaces

    • Image manipulation

    • Rendering

• Human-centered computing

  • Human computer interaction (HCI)

    • Interaction devices

      • Graphics input devices