Abstract
A recently developed quantitative model describing the dynamical response characteristics of primate cones is used for rendering high dynamic range (HDR) video. The model provides range compression, as well as luminance-dependent noise suppression. The steady-state (static) version of the model provides a global tone mapping algorithm for rendering HDR images. Both the static and dynamic cone models can be inverted, enabling expansion of the HDR images and video that were compressed with the cone model.
Supplemental Material
- Ashikhmin M. 2002. A tone mapping algorithm for high contrast images. In EGWR: Proceedings of the 13th Eurographics Workshop on Rendering. 145--156. Google Scholar
- Artusi A., Bittner, J., Wimmer, M., and Wilkie, A. 2003. Delivering interactivity to complex tone mapping operators. In EGSR: Proceedings of the 14th Eurographics Symposium on Rendering. 38--44. Google Scholar
- Baxter, B. S., Ravindra, H., and Normann, R. A. 1982. Changes in lesion detectability caused by light adaptation in retinal photoreceptors. Investigative Radiology 17, 394--401.Google Scholar
- Bennett, E. P. and Mcmillan, L. 2005. Video enhancement using per-pixel virtual exposures. ACM Trans. Graph. 24, 3, 845--852. Google Scholar
- Boynton, R. M. and Kambe, N. 1980. Chromatic difference steps of moderate size measured along theoretically critical axes. Color Res. Appl. 5, 13--23.Google Scholar
- Brown, K. S. 2000. Lead-Lag algorithms. http://www.mathpages.com/home/kmath198/kmath198.htm.Google Scholar
- Daly, S. 1993. The visible differences predictor: An algorithm for the assessment of image fidelity. In Digital Images and Human Vision. A.B. WATSON, Ed. MIT Press, Cambridge, MA. 179--206. Google Scholar
- Debevec, P. E. 1998. Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global illumination and high dynamic range photography. Computer Graphics Annual Conference Series (SIGGRAPH). 189--198. Google Scholar
- DelbrüCk, T. and Mascarenhas, S. M. 1997. Notes on practical photometry. http://www.ini.unizh.ch/~tobi/anaprose/recep/practicalPhotometry.pdf.Google Scholar
- Devlin, K. 2002. A review of tone reproduction techniques. Tech. Rep. CSTR-02-005, Department of Computer Science, University of Bristol.Google Scholar
- Durand, F. and Dorsey, J. 2000. Interactive tone mapping. In Proceedings of the Eurographics Workshop on Rendering Techniques. 219--230. Google Scholar
- Durand, F. and Dorsey, J. 2002. Fast bilateral filtering for the display of high-dynamic-range images. In Computer Graphics Annual Conference Series (SIGGRAPH), 257--266. Google Scholar
- Fain, G. L., Matthews, H. R., Cornwall, M. C., and Koutalos, Y. 2001. Adaptation in vertebrate photoreceptors. Physiological Rev. 81, 117--151.Google Scholar
- Fattal, R., Lischinski, D., and Werman, M. 2002. Gradient domain high dynamic range compression. ACM Trans. Graph. 21, 249--256. Google Scholar
- 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 the 23rd Annual Conference on Computer Graphics and Interactive Techniques. 249--258. Google Scholar
- Irawan, P., Ferwerda, J. A., and Marschner, S. R. 2005. Perceptually-Based tone mapping of high dynamic range image streams. In EGSR: Proceedings of the 16th Eurographics Symposium on Rendering. 231--242. Google Scholar
- Krawczyk, G., Myszkowski, K., and Seidel, H.-P. 2005. Lightness perception in tone reproduction for high dynamic range images. Comput. Graph. Forum 24, 3, 635--645.Google Scholar
- Laughlin, S. B. 1983. Matching coding to scenes to enhance efficiency. In Physical and Biological Processing of Images. O. J. BRADDICK, AND A. C. SLEIGH, Eds. Springer, New York. 42--52.Google Scholar
- Ledda, P., Santos, L. P., and Chalmers, A. 2004. A local model of eye adaptation for high dynamic range images. In Proceedings of the 3rd International Conference on Computer Graphics, Virtual Reality, and Visualisation. 151--160. Google Scholar
- Lee, B. B., Dacey, D. M., Smith, V. C., and Pokorny, J. 1999. Horizontal cells reveal cone type-specific adaptation in primate retina. Proceedings of the National Academy of Science U.S.A., 96, 14611--14616.Google Scholar
- Lee, B. B., Dacey, D. M., Smith, V. C., and Pokorny, J. 2003. Dynamics of sensitivity regulation in primate outer retina: The horizontal cell network. J. Vision 3, 513--526.Google Scholar
- Li, Y., Sharan, L., and Adelson, E. H. 2005. Compressing and companding high dynamic range images with subband architectures. In ACM Trans. Graph. 24, 3, 836--844. Google Scholar
- Macleod, D. I. A., Williams, D. R., and Makous, W. 1992. A visual nonlinearity fed by single cones. Vision Res. 32, 347--363.Google Scholar
- Mantiuk, R., Krawczyk, G., Myszkowski, K., and Seidel, H.-P. 2004. Perception-Motivated high dynamic range video encoding. ACM Trans. Graph. 23, 731--741. Google Scholar
- Nikonov, S., Lamb, T. D., and Pugh, E. N., Jr. 2000. The role of steady phosphodiesterase activity in the kinetics and sensitivity of the light-adapted salamander rod photoresponse. J. General Physiology 116, 795--824.Google Scholar
- Normann, R. A., Baxter, B. S., Ravindra, H., and Anderton, P. J. 1983. Photoreceptor contributions to contrast sensitivity: Applications in radiological diagnosis. IEEE Trans. Syst. Man Cybernetics 13, 944--953.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. In Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques. 287--298. Google Scholar
- Pattanaik, S. N., Tumblin, J., Yee, H., and Greenberg, D. P. 2000. Time-Dependent visual adaptation for fast realistic image display. In Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques. 47--54. Google Scholar
- Poynton, C. 1996. Gamma. In A Technical Introduction to Digital Video. JohnWiley, New York. http://www.poynton.com/notes/TIDV/index.html. Google Scholar
- Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. 1992. Numerical Recipes in Fortran. Cambridge University Press, New York. Google Scholar
- Pugh, E. N., Jr. and Lamb, T. D. 2000. Phototransduction in vertebrate rods and cones: Molecular mechanisms of amplification, recovery and light adaptation. In Handbook of Biological Physics, vol. 3. D. G. STAVENGA et al. Eds. Elsevier, Amsterdam. 183--254.Google Scholar
- Reinhard, E. and Devlin, K. 2005. Dynamic range reduction inspired by photoreceptor physiology. IEEE Trans. Visualization Comput. Graph. 11, 13--24. Google Scholar
- Reinhard, E., Ward, G., Pattanaik, S., and Debevec, P. 2005. High Dynamic Range Imaging: Acquisition, Display, and Image-Based Rendering. Morgan Kaufmann, San Francisco, CA. Google Scholar
- Richards, W. A. 1982. Lightness scale from image intensity distributions. Appl. Optics 21, 2569--2582.Google Scholar
- Scheel, A., Stamminger, M., and Seidel, H.-P. 2000. Tone reproduction for interactive walkthroughs. Comput. Graph. Forum 19, 3, 301--312.Google Scholar
- Schneeweis, D. M., and Schnapf, J. L. 1999. The photovoltage of macaque cone photoreceptors: Adaptation, noise, and kinetics. J. Neurosci. 19, 1203--1216.Google Scholar
- Shannon, D. E. 1948. The mathematical theory of communication. Bell Syst. Tech. J. 27, 3--91.Google Scholar
- Smith, N. P., and Lamb, T. D. 1997. The a-wave of the human electroretinogram recorded with a minimally invasive technique. Vision Res. 37, 2943--2952.Google Scholar
- Smith, V. C., Pokorny, J., Lee, B. B., and Dacey, D. M. 2001. Primate horizontal cell dynamics: An analysis of sensitivity regulation in the outer retina. J. Neurophysiology. 85, 545--558.Google Scholar
- Tumblin, J., Hodgins, J. K., and Guenther, B. K. 1999. Two methods for display of high contrast images. ACM Trans. Graph. 18, 56--94. Google Scholar
- Van Der Schaaf, A. 1998. Natural image statistics and visual processing. PhD thesis, University of Groningen. http://irs.ub.rug.nl/ppu/166956252.Google Scholar
- Van Hateren, J. H. 2005. A cellular and molecular model of response kinetics and adaptation in primate cones and horizontal cells. J. Vision 5, 331--347.Google Scholar
- Van Hateren, J. H. and Lamb, T. D. 2006. The photocurrent response of human cones is fast and monophasic. BMC Neurosci. 7, 34.Google Scholar
- Van Hateren, J. H., RÜTtiger, L., Sun, H., and Lee B. B. 2002. Processing of natural temporal stimuli by macaque retinal ganglion cells. J. Neurosci. 22, 9945--9960.Google Scholar
- Van Hateren, J. H. and Van Der Schaaf, A. 1996. Temporal properties of natural scenes. In Proceedings of the IS and T/SPIE Conference on Electronic Imaging: Science & Technology. San Jose, CA. 139--143.Google Scholar
- Ward Larson, G. J. 1994. The RADIANCE lighting simulation and rendering system. In Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques. 459--472. Google Scholar
- Ward Larson, G. J., Rushmeier, H., and Piatko, C. 1997. A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Trans. Visualization Comput. Graph. 3, 291--306. Google Scholar
- Westheimer, G. 1986. The eye as an optical instrument. In Handbook of Perception and Human Performance. K. R. Boff, et al., Eds. John Wiley, New York.Google Scholar
- Wyszecki, G. and Stiles, W. S. 1982. Color Science. John Wiley, New York.Google Scholar
Index Terms
- Encoding of high dynamic range video with a model of human cones
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