Abstract
One may wish to use computer graphic images to carry out road visibility studies. Unfortunately, most display devices still have a limited luminance dynamic range, especially in driving simulators. In this paper, we propose a tone-mapping operator (TMO) to compress the luminance dynamic range while preserving the driver's performance for a visual task relevant for a driving situation. We address three display issues of some consequences for road image display: luminance dynamics, image quantization, and high minimum displayable luminance. Our TMO characterizes the effects of local adaptation with a bandpass decomposition of the image using a Laplacian pyramid, and processes the levels separately in order to mimic the human visual system. The contrast perception model uses the visibility level, a usual index in road visibility engineering applications. To assess our algorithm, a psychophysical experiment devoted to a target detection task was designed. Using a Landolt ring, the visual performances of 30 observers were measured: they stared first at a high-dynamic range image and then at the same image processed by a TMO and displayed on a low-dynamic range monitor, for comparison. The evaluation was completed with a visual appearance evaluation. Our operator gives good performances for three typical road situations (one in daylight and two at night), after comparison with four standard TMOs from the literature. The psychovisual assessment of our TMO is limited to these driving situations.
- Adrian, W. 1989. Visibility of targets: model for calculation. Lighting Research and Technology 21, 181--188.Google ScholarCross Ref
- Brémond, R. and Gallée, G. 2002. Image quality for driving simulation experiments. In Proc. of Driving Simulation Conference 2002. INRETS-Renault.Google Scholar
- Burt, P. J. and Adelson, E. H. 1983. The laplacian pyramid as a compact image code. IEEE Transactions on Communications 31, 4 (Ap.), 532--540.Google ScholarCross Ref
- Campbell, F. and Robson, J. 1968. Application of fourier analysis to the visibility of gratings. Journal of Physiology 197, 551--566.Google ScholarCross Ref
- CIE. 1981. An Analytic Model for Describing the Influence of Lighting Parameters upon Visual Performance. Report 19/2.1. Commission Internationale de l'Eclairage.Google Scholar
- CIE. 1988. Roadsigns. Report 74. Commission Internationale de l'Eclairage.Google Scholar
- CIE. 1992. Contrast and Visibility. Report 95. Commission Internationale de l'Eclairage.Google Scholar
- CIE. 1996. The Relationship between Digital and Colorimetric Data for Computer-Controlled CRT Displays. Report 122. Commission Internationale de l'Eclairage.Google Scholar
- CIE. 1999. Visual Adaptation to Complex Luminance Distribution. Report 135/5. Commission Internationale de l'Eclairage.Google Scholar
- Drago, F., Martens, W. L., Myszkowski, K., and Seidel, H.-P. 2003. Perceptual evaluation of tone mapping operators. In ACM SIGGRAPH 2003 Sketches & Applications. ACM Press, New York. 1--1. Google ScholarDigital Library
- Dupuis, M. and Grezlikowski, H. 2006. Opendrive, an open standard for the description of roads for driving simulations. In Proceedings of the Driving Simulation Europe. INRETS-Renault, 25--36.Google Scholar
- Ferwerda, J. A. 2001. Elements of early vision for computer graphics. In IEEE computer graphics and applications. IEEE, Los Alamitos, CA. 21--33. Google ScholarDigital Library
- Ferwerda, J. A., Pattanaik, S. N., Shirley, P., and Greenberg, D. P. 1996. A model of visual adaptation for realistic image synthesis. In Proceedings of ACM SIGGRAPH '96. ACM, New York. 249--258. Google ScholarDigital Library
- Ginsburg, A. P. 1986. Chapter 34: spatial filtering and visual form perception. In Handbook of Perception and Visual Performance, K. R. Boff, L. Kaufmann, and J. P. Thomas, Eds. Wiley, New York. 1--41.Google Scholar
- Grave, J. and Brémond, R. 2005. Designing a tone mapping algorithm for road visibility experiments. In APGV '05: Proceedings of the 2nd Symposium on Applied Perception in Graphics and Visualization. ACM Press, New York. 168. Google ScholarDigital Library
- Hills, B. L. 1980. Vision, visibility, and perception in driving. Perception 9, 183--216.Google ScholarCross Ref
- Hoc, J.-M. 2001. Towards ecological validity of research in cognitive ergonomics. Theoretical Issues in Ergonomic Science 2, 3, 278--288.Google ScholarCross Ref
- Ishida, T. and Iriyama, K. 2003. Estimating light adaptation levels for visual environments with complicated luminance distribution. In Proceedings of the 25th Session of CIE. D, vol. 1. CIE. 10--13.Google Scholar
- Kelly, D. H. 1985. Visual processing of moving stimuli. In Journal of the Optical Society of America. 2, vol. 2. 216--225.Google Scholar
- Kuang, J., Yamaguchi, H., Johnson, G., and Fairchild, M. 2004. Testing hdr image rendering algorithms. In Proceedings of IS and T/SID 12th Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications. SID, 315--320.Google Scholar
- 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 Compter Graphics. 291--306. Google ScholarDigital Library
- Ledda, P., Santos, L. P., and Chalmers, A. 2004. A local model of eye adaptation for high dynamic range images. In AFRIGRAPH '04: Proceedings of the 3rd International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa. ACM Press, New York. 151--160. Google ScholarDigital Library
- Ledda, P., Chalmers, A., Troscianko, T., and Seetzen, H. 2005. Evaluation of tone mapping operators using a high dynamic range display. In Proceedings of ACM SIGGRAPH '05. 249--258. Google ScholarDigital Library
- Li, Y., Sharan, L., and Adelson, E. H. 2005. Compressing and companding high dynamic range images with subband architectures. ACM Transactions on Graphics 24, 3, 836--844. Google ScholarDigital Library
- Moon, P. and Spencer, D. 1945. The visual effect of non-uniform surrounds. Journal of the Optical Society of America 35, 3, 233--248.Google ScholarCross Ref
- MOVE. 2005. Performance based model for mesopic photometry. Helsinki University of Technology.Google Scholar
- 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. Computer Graphics 32, Annual Conference Series. 287--298. Google ScholarDigital Library
- Pattanaik, S. N., Tumblin, J., Yee, H., and Greenberg, D. P. 2000. Time-dependent visual adaptation for fast realistic image display. In In Proceedings of ACM SIGGRAPH 2000. ACM, New York. 47--54. Google ScholarDigital Library
- Peli, E. 1990. Contrast in complex images. Journal of the Optical Society of America 7, 1 (Oct.), 2032--2040.Google Scholar
- Reinhard, E., Stark, M., Shirley, P., and Ferwerda, J. 2002. Photographic tone reproduction for digital images. In Proceedings of ACM SIGGRAPH 2002. 267--276. Google ScholarDigital Library
- Reinhard, E., Ward, G., Pattanaik, S., and Debevec, P. 2005. High dynamic range imaging: acquisition, display, and image based lighting. Morgan Kaufmann. Google ScholarDigital Library
- Seetzen, H., Heidrich, W., Stuerzlinger, W., Ward, G., Whitehead, L., Trentacoste, M., Ghosh, A., and Vorozcovs, A. 2004. High dynamic range display systems. In Proceedings SIGGRAPH 2004. 3, vol. 23. 760--768. Google ScholarDigital Library
- Shapley, R. 1991. Chapter 12: Neural mechanisms of contrast sensitivity. In Spatial Vision, D. M. Regan, Ed., MacMillon, New York. 290--306.Google Scholar
- Smith, K., Krawczyk, G., Myszkowski, K., and Seidel, H.-P. 2006. Beyond tone mapping: Enhanced depiction of tone mapped hdr images. In Computer Graphics Forum, Proceedings of Eurographics 2006. 3, vol. 25. Eurographics, 427--438.Google Scholar
- Spencer, G., Shirley, P., Zimmerman, K., and Greenberg, D. 1995. Physically-based glare effects for computer generated images. Proceedings ACM SIGGRAPH '95. 325--334. Google ScholarDigital Library
- Viénot, F., Boust, C., Costa, E. D., Brémond, R., and Dumont, E. 2002. Psychometric assessment of the look and feel of digital images. In Driving Simulation Conference. INRETS-Renault.Google Scholar
- Ward, G. 1994. A contrast-based scalefactor for luminance display. Graphics Gems IV, 415--421. Google ScholarDigital Library
- Yoshida, A., Blanz, V., Myszkowski, K., and Seidel, H.-P. 2005. Perceptual evaluation of tone mapping operators with real-world scenes. In Human Vision and Electronic Imaging X, IS& T/SPIE's 17th Annual Symposium on Electronic Imaging. SPIE Proceedings Series, vol. 5666. San Jose, CA. 192--203.Google Scholar
- Yoshida, A., Mantiuk, R., Myszkowski, K., and Seidel, H.-P. 2006. Analysis of reproducing real-world appearance on displays of varying dynamic range. In Computer Graphics Forum, Proceedings of Eurographics 2006. 3, vol. 25. Eurographics, 415--426.Google Scholar
Index Terms
- A tone-mapping operator for road visibility experiments
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