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Fast bilateral filtering for the display of high-dynamic-range images

Published:01 July 2002Publication History
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Abstract

We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. Only the base layer has its contrast reduced, thereby preserving detail. The base layer is obtained using an edge-preserving filter called the bilateral filter. This is a non-linear filter, where the weight of each pixel is computed using a Gaussian in the spatial domain multiplied by an influence function in the intensity domain that decreases the weight of pixels with large intensity differences. We express bilateral filtering in the framework of robust statistics and show how it relates to anisotropic diffusion. We then accelerate bilateral filtering by using a piecewise-linear approximation in the intensity domain and appropriate subsampling. This results in a speed-up of two orders of magnitude. The method is fast and requires no parameter setting.

References

  1. ADAMS, A. 1995. The Camera+The Negative+The Print. Little Brown and Co.Google ScholarGoogle Scholar
  2. BARASH, D. 2001. A fundamental relationship between bilateral filtering, adaptive smoothing and the nonlinear diffusion equation. IEEE PAMI. in press. Google ScholarGoogle Scholar
  3. BARROW, H., AND TENENBAUM, J. 1978. Recovering intrinsic scene characteristics from images. In Computer Vision Systems. Academic Press, New York, 3-26.Google ScholarGoogle Scholar
  4. BLACK, M., SAPIRO, G., MARIMONT, D., AND HEEGER, D. 1998. Robust anisotropic diffusion. IEEE Trans. Image Processing 7, 3 (Mar.), 421-432. Google ScholarGoogle Scholar
  5. CHIU, K., HERF, M., SHIRLEY, P., SWAMY, S., WANG, C., AND ZIMMERMAN, K. 1993. Spatially nonuniform scaling functions for high contrast images. In Proc. Graphics Interface, 245-253.Google ScholarGoogle Scholar
  6. COHEN, J., TCHOU, C., HAWKINS, T., AND DEBEVEC, P. 2001. Real-time high-dynamic range texture mapping. In Rendering Techniques 2001: 12th Eurographics Workshop on Rendering, Eurographics, 313-320. Google ScholarGoogle Scholar
  7. DEBEVEC, P. E., AND MALIK, J. 1997. Recovering high dynamic range radiance maps from photographs. In Proceedings of SIGGRAPH 97, ACM SIGGRAPH / Addison Wesley, Los Angeles, California, Computer Graphics Proceedings, Annual Conference Series, 369-378. Google ScholarGoogle Scholar
  8. DESBRUN, M., MEYER, M., SCHRÖDER, P., AND BARR, A. H. 2000. Anisotropic feature-preserving denoising of height fields and bivariate data. In Graphics Interface, 145-152.Google ScholarGoogle Scholar
  9. DICARLO, J., AND WANDELL, B. 2000. Rendering high dynamic range images. Proceedings of the SPIE: Image Sensors 3965, 392-401.Google ScholarGoogle Scholar
  10. DURAND, F. 2002. An invitation to discuss computer depiction. In Proc. NPAR'02. Google ScholarGoogle Scholar
  11. ELAD, M. to appear. On the bilateral filter and ways to improve it. IEEE Trans. on Image Processing. Google ScholarGoogle Scholar
  12. FERWERDA, J. 1998. Fundamentals of spatial vision. In Applications of visual perception in computer graphics. Siggraph '98 Course Notes.Google ScholarGoogle Scholar
  13. HAMPEL, F. R., RONCHETTI, E. M., ROUSSEEUW, P. J., AND STAHEL, W. A. 1986. Robust Statistics: The Approach Based on Influence Functions. Wiley, New York.Google ScholarGoogle Scholar
  14. HUBER, P. J. 1981. Robust Statistics. John Wiley and Sons, New York.Google ScholarGoogle Scholar
  15. JOBSON, RAHMAN, AND WOODELL. 1997. A multi-scale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. on Image Processing: Special Issue on Color Processing 6 (July), 965-976. Google ScholarGoogle Scholar
  16. LARSON, G. W., 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 (October - December), 291-306. Google ScholarGoogle Scholar
  17. MADDEN, B. 1993. Extended intensity range imaging. Tech. rep., U. of Pennsylvania, GRASP Laboratory.Google ScholarGoogle Scholar
  18. MCCOOL, M. 1999. Anisotropic diffusion for monte carlo noise reduction. ACM Trans. on Graphics 18, 2, 171-194. Google ScholarGoogle Scholar
  19. MITSUNAGA, T., AND NAYAR, S. K. 2000. High dynamic range imaging: Spatially varying pixel exposures. In IEEE CVPR, 472-479.Google ScholarGoogle Scholar
  20. OH, B. M., CHEN, M., DORSEY, J., AND DURAND, F. 2001. Image-based modeling and photo editing. In Proceedings of ACM SIGGRAPH 2001, ACM Press / ACM SIGGRAPH, Computer Graphics Proceedings, Annual Conference Series, 433-442. Google ScholarGoogle Scholar
  21. 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 Proceedings of SIGGRAPH 98, ACM SIGGRAPH / Addison Wesley, Orlando, Florida, Computer Graphics Proceedings, Annual Conference Series, 287-298. Google ScholarGoogle Scholar
  22. PERONA, P., AND MALIK, J. 1990. Scale-space and edge detection using anisotropic diffusion. IEEE PAMI 12, 7, 629-639. Google ScholarGoogle Scholar
  23. RUDMAN, T. 2001. The Photographer's Master Printing Course. Focal Press.Google ScholarGoogle Scholar
  24. RUSHMEIER, H. E., AND WARD, G. J. 1994. Energy preserving non-linear filters. In Proceedings of SIGGRAPH 94, ACM SIGGRAPH / ACM Press, Orlando, Florida, Computer Graphics Proceedings, Annual Conference Series, 131-138. Google ScholarGoogle Scholar
  25. SAINT-MARC, P., CHEN, J., AND MEDIONI, G., 1991. Adaptive smoothing: a general tool for early vision.Google ScholarGoogle Scholar
  26. SCHECHNER, Y. Y., AND NAYAR, S. K. 2001. Generalized mosaicing. In Proc. IEEE CVPR, 17-24.Google ScholarGoogle Scholar
  27. SCHLICK, C. 1994. Quantization techniques for visualization of high dynamic range pictures. 5th Eurographics Workshop on Rendering, 7-20.Google ScholarGoogle Scholar
  28. SOCOLINSKY, D. 2000. Dynamic range constraints in image fusion and visualization. In Proc. Signal and Image Processing.Google ScholarGoogle Scholar
  29. TOMASI, C., AND MANDUCHI, R. 1998. Bilateral filtering for gray and color images. In Proc. IEEE Int. Conf. on Computer Vision, 836-846. Google ScholarGoogle Scholar
  30. TUMBLIN, J., AND RUSHMEIER, H. 1993. Tone reproduction for realistic images. IEEE Comp. Graphics & Applications 13, 6, 42-48. Google ScholarGoogle Scholar
  31. TUMBLIN, J., AND TURK, G. 1999. Lcis: A boundary hierarchy for detail-preserving contrast reduction. In Proceedings of SIGGRAPH 99, ACM SIGGRAPH / Addison Wesley Longman, Los Angeles, California, Computer Graphics Proceedings, Annual Conference Series, 83-90. Google ScholarGoogle Scholar
  32. TUMBLIN, J., HODGINS, J., AND GUENTER, B. 1999. Two methods for display of high contrast images. ACM Trans. on Graphics 18, 1, 56-94. Google ScholarGoogle Scholar
  33. TUMBLIN, J. 1999. Three methods of detail-preserving contrast reduction for displayed images. PhD thesis, College of Computing Georgia Inst. of Technology. Google ScholarGoogle Scholar
  34. WARD, G. J. 1994. The radiance lighting simulation and rendering system. In Proceedings of SIGGRAPH 94, ACM SIGGRAPH / ACM Press, Orlando, Florida, Computer Graphics Proceedings, Annual Conference Series, 459-472. Google ScholarGoogle Scholar
  35. YANG, D., GAMAL, A. E., FOWLER, B., AND TIAN, H. 1999. A 640x512 cmos image sensor with ultrawide dynamic range floating-point pixel-level adc. IEEE Journal of Solid State Circuits 34, 12 (Dec.), 1821-1834.Google ScholarGoogle Scholar

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