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Photographic tone reproduction for digital images

Published:01 July 2002Publication History

ABSTRACT

A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and produces good results for a wide variety of images.

References

  1. ADAMS, A. 1980. The camera. The Ansel Adams Photography series. Little, Brown and Company.Google ScholarGoogle Scholar
  2. ADAMS, A. 1981. The negative. The Ansel Adams Photography series. Little, Brown and Company.Google ScholarGoogle Scholar
  3. ADAMS, A. 1983. The print. The Ansel Adams Photography series. Little, Brown and Company.Google ScholarGoogle Scholar
  4. BLOMMAERT, F. J. J., AND MARTENS, J.-B. 1990. An object-oriented model for brightness perception. Spatial Vision 5, 1, 15-41.Google ScholarGoogle ScholarCross RefCross Ref
  5. BURT, P. J., AND ADELSON, E. H. 1983. A multiresolution spline with application to image mosaics. ACM Transactions on Graphics 2, 4, 217-236. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. CHIU, K., HERF, M., SHIRLEY, P., SWAMY, S., WANG, C., AND ZIMMERMAN, K. 1993. Spatially nonuniform scaling functions for high contrast images. In Proceedings of Graphics Interface '93, 245-253.Google ScholarGoogle Scholar
  7. COHEN, J., TCHOU, C., HAWKINS, T., AND DEBEVEC, P. 2001. Real-Time high dynamic range texture mapping. In Rendering techniques 2001, S. J. Gortler and K. Myszkowski, Eds., 313-320. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. DEBEVEC, P. E., AND MALIK, J. 1997. Recovering high dynamic range radiance maps from photographs. In SIGGRAPH 97 Conference Proceedings, Addison Wesley, T. Whitted, Ed., Annual Conference Series, ACM SIGGRAPH, 369-378. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. DURAND, F., AND DORSEY, J. 2000. Interactive tone mapping. In Eurographics Workshop on Rendering, 219-230. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. FAIRCHILD, M. D. 1998. Color appearance models. Addison-Wesley, Reading, MA.Google ScholarGoogle Scholar
  11. FERWERDA, J. A., PATTANAIK, S., SHIRLEY, P., AND GREENBERG, D. P. 1996. A model of visual adaptation for realistic image synthesis. In SIGGRAPH 96 Conference Proceedings, Addison Wesley, H. Rushmeier, Ed., Annual Conference Series, ACM SIGGRAPH, 249-258. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. GEIGEL, J., AND MUSGRAVE, F. K. 1997. A model for simulating the photographic development process on digital images. In SIGGRAPH 97 Conference Proceedings, Addison Wesley, T. Whitted, Ed., Annual Conference Series, ACM SIGGRAPH, 135-142. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. GOVE, A., GROSSBERG, S., AND MINGOLLA, E. 1995. Brightness perception, illusory contours, and corticogeniculate feedback. Visual Neuroscience 12, 1027-1052.Google ScholarGoogle ScholarCross RefCross Ref
  14. GRAVES, C. 1997. The zone system for 35mm photographers, second ed. Focal Press.Google ScholarGoogle Scholar
  15. HANSEN, T., BARATOFF, G., AND NEUMANN, H. 2000. A simple cell model with dominating opponent inhibition for robust contrast detection. Kognitionswissenschaft 9, 93-100. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. HOLM, J. 1996. Photographics tone and colour reproduction goals. In CIE Expert Symposium '96 on Colour Standards for Image Technology, 51-56.Google ScholarGoogle Scholar
  17. JERNIGAN, M. E., AND MCLEAN, G. F. 1992. Lateral inhibition and image processing. In Non-linear vision: determination of neural receptive fields, function, and networks, R. B. Pinter and B. Nabet, Eds. CRC Press, ch. 17, 451-462.Google ScholarGoogle Scholar
  18. JOHNSON, C. 1999. The practical zone system. Focal Press.Google ScholarGoogle Scholar
  19. LAND, E. H., AND MCCANN, J. J. 1971. Lightness and retinex theory. J. Opt. Soc. Am. 63, 1, 1-11.Google ScholarGoogle ScholarCross RefCross Ref
  20. LONDON, B., AND UPTON, J. 1998. Photography, sixth ed. Longman.Google ScholarGoogle Scholar
  21. MARR, D., AND HILDRETH, E. C. 1980. Theory of edge detection. Proceedings of the Royal Society of London, B 207, 187-217.Google ScholarGoogle ScholarCross RefCross Ref
  22. MARR, D. 1982. Vision, a computational investigation into the human representation and processing of visual information. W H Freeman and Company, San Fransisco. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. MATKOVIC, K., NEUMANN, L., AND PURGATHOFER, W. 1997. A survey of tone mapping techniques. In 13th Spring Conference on Computer Graphics, W. Straßer, Ed., 163-170.Google ScholarGoogle Scholar
  24. MCNAMARA, A., CHALMERS, A., AND TROSCIANKO, T. 2000. STAR: Visual perception in realistic image synthesis. In Eurographics 2000 STAR reports, Eurographics, Interlaken, Switzerland.Google ScholarGoogle Scholar
  25. MCNAMARA, A. 2001. Visual perception in realistic image synthesis. Computer Graphics Forum 20, 4 (December), 211-224.Google ScholarGoogle ScholarCross RefCross Ref
  26. MILLER, N. J., NGAI, P. Y., AND MILLER, D. D. 1984. The application of computer graphics in lighting design. Journal of the IES 14 (October), 6-26.Google ScholarGoogle Scholar
  27. MITCHELL, E. N. 1984. Photographic Science. John Wiley and Sons, New York.Google ScholarGoogle Scholar
  28. OPPENHEIM, A. V., SCHAFER, R., AND STOCKHAM, T. 1968. Nonlinear filtering of multiplied and convolved signals. Proceedings of the IEEE 56, 8, 1264-1291.Google ScholarGoogle ScholarCross RefCross Ref
  29. PARDO, A., AND SAPIRO, G. 2001. Visualization of high dynamic range images. Tech. Rep. 1753, Institute for Mathematics and its Applications, University of Minnesota.Google ScholarGoogle Scholar
  30. PATTANAIK, S. N., FERWERDA, J. A., FAIRCHILD, M. D., AND GREENBERG, D. P. 1998. A multiscale model of adaptation and spatial vision for realistic image display. In SIGGRAPH 98 Conference Proceedings, Addison Wesley, M. Cohen, Ed., Annual Conference Series, ACM SIGGRAPH, 287-298. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. PATTANAIK, S. N., TUMBLIN, J., YEE, H., , AND GREENBERG, D. P. 2000. Time-dependent visual adaptation for fast realistic display. In SIGGRAPH 2000 Conference Proceedings, Addison Wesley, K. Akeley, Ed., Annual Conference Series, ACM SIGGRAPH, 47-54. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. PELI, E. 1990. Contrast in complex images. J. Opt. Soc. Am. A 7, 10 (October), 2032-2040.Google ScholarGoogle ScholarCross RefCross Ref
  33. PESSOA, L., MINGOLLA, E., AND NEUMANN, H. 1995. A contrast- and luminance-driven multiscale network model of brightness perception. Vision Research 35, 15, 2201-2223.Google ScholarGoogle ScholarCross RefCross Ref
  34. RAHMAN, Z., JOBSON, D. J., AND WOODELL, G. A. 1996. A multiscale retinex for color rendition and dynamic range compression. In SPIE Proceedings: Applications of Digital Image Processing XIX, vol. 2847.Google ScholarGoogle ScholarCross RefCross Ref
  35. RAHMAN, Z., WOODELL, G. A., AND JOBSON, D. J. 1997. A comparison of the multiscale retinex with other image enhancement techniques. In IS&T's 50th Annual Conference: A Celebration of All Imaging, vol. 50, 426-431.Google ScholarGoogle Scholar
  36. REINHARD, E., ASHIKHMIN, M., GOOCH, B., AND SHIRLEY, P. 2001. Color transfer between images. IEEE Computer Graphics and Applications 21 (September/October), 34-41. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. SCHEEL, A., STAMMINGER, M., AND SEIDEL, H.-P. 2000. Tone reproduction for interactive walkthroughs. Computer Graphics Forum 19, 3 (August), 301-312.Google ScholarGoogle ScholarCross RefCross Ref
  38. SCHLICK, C. 1994. Quantization techniques for the visualization of high dynamic range pictures. In Photorealistic Rendering Techniques, Springer-Verlag Berlin Heidelberg New York, P. Shirley, G. Sakas, and S. Müller, Eds., 7-20.Google ScholarGoogle Scholar
  39. STOCKHAM, T. 1972. Image processing in the context of a visual model. Proceedings of the IEEE 60, 7, 828-842.Google ScholarGoogle ScholarCross RefCross Ref
  40. STROEBEL, L., COMPTON, J., CURRENT, I., AND ZAKIA, R. 2000. Basic photographic materials and processes, second ed. Focal Press.Google ScholarGoogle Scholar
  41. TUMBLIN, J., AND RUSHMEIER, H. 1991. Tone reproduction for realistic computer generated images. Tech. Rep. GIT-GVU-91-13, Graphics, Visualization, and Useability Center, Georgia Institute of Technology.Google ScholarGoogle Scholar
  42. TUMBLIN, J., AND RUSHMEIER, H. 1993. Tone reproduction for computer generated images. IEEE Computer Graphics and Applications 13, 6 (November), 42-48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. TUMBLIN, J., AND TURK, G. 1999. LCIS: A boundary hierarchy for detail-preserving contrast reduction. In Siggraph 1999, Computer Graphics Proceedings, Addison Wesley Longman, Los Angeles, A. Rockwood, Ed., Annual Conference Series, 83-90. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. TUMBLIN, J., HODGINS, J. K., AND GUENTER, B. K. 1999. Two methods for display of high contrast images. ACM Transactions on Graphics 18 (1), 56-94. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. UPSTILL, S. 1985. The Realistic Presentation of Synthetic Images: Image Processing in Computer Graphics. PhD thesis, University of California at Berkeley. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. WARD, G., RUSHMEIER, H., AND PIATKO, C. 1997. A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Transactions on Visualization and Computer Graphics 3, 4 (December). Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. WARD LARSON, G., AND SHAKESPEARE, R. A. 1998. Rendering with Radiance. Morgan Kaufmann Publishers.Google ScholarGoogle Scholar
  48. WARD, G. 1994. A contrast-based scalefactor for luminance display. In Graphics Gems IV, P. Heckbert, Ed. Academic Press, Boston, 415-421. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. WHITE, M., ZAKIA, R., AND LORENZ, P. 1984. The new zone system manual. Morgan & Morgan, Inc.Google ScholarGoogle Scholar
  50. WOODS, J. C. 1993. The zone system craftbook. McGraw Hill.Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Conferences
      SIGGRAPH '02: Proceedings of the 29th annual conference on Computer graphics and interactive techniques
      July 2002
      574 pages
      ISBN:1581135211
      DOI:10.1145/566570

      Copyright © 2002 ACM

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      • Published: 1 July 2002

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