Abstract
We investigate applications of the Visible Difference Predictor (VDP) to steer global illumination computation. We use the VDP to monitor the progression of computation as a function of time for major global illumination algorithms. Based on the results obtained, we propose a novel global illumination algorithm which is a hybrid of stochastic (density estimation) and deterministic (adaptive mesh refinement) techniques used in an optimized sequence to reduce the differences between the intermediate and final images as predicted by the VDP. Also, the VDP is applied to decide upon stopping conditions for global illumination simulation, when further continuation of computation does not contribute to perceivable changes in the quality of the resulting
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References
M.R. Bolin and G.W. Meyer. A Perceptually Based Adaptive Sampling Algorithm. In Proc.of Siggraph’98, 299–310, 1998
P.K. Burt. Fast filter transforms for image processing. Computer Vision, Graphics and Image Processing, 21:368–382, 1981.
M.F, Cohen, D.P. Greenberg, D.S. Immel, and P.J. Brock. An efficient radiosity approach for realistic image synthesis. IEEE Computer Graphics and Applications, 6(3):26–35, March 1986.
M.F. Cohen, S.E. Chen, J.R. Wallace, and D.P. Greenberg. A progressive refinement approach to fast radiosity image generation. In Proc. of Siggraph’88, pages 75–84, 1988.
S. Comes, O. Bruyndonckx, and B. Macq. Image quality criterion based on the cancellation of the masked noise. In Proc. of IEEE Int’l Conference on Acoustics, Speech and Signal Processing, pages 2635–2638,1995.
S. Daly. The Visible Differences Predictor: An algorithm for the assessment of image fidelity. In A.B. Watson, editor, Digital Image and Human Vision, pages 179–206. Cambridge, Ma: MIT Press, 1993.
R.L. De Valois and De Valois K.K. Spatial vision. Oxforf University Press, Oxford, 1990.
G. Drettakis and F.X. Sillion. Accurate visibility and meshing calculations for hierarchical radiosity. In X. Pueyo and P. Schroder, editors, Rendering Techniques’ 96, pages 269–278. Springer, June 1996.
J.A. Ferwerda, S. Pattanaik, P. Shirley, and D.P. Greenberg. A model of visual masking for computer graphics. In Proc. of Siggraph’97, pages 143–152, 1997.
A. Gaddipatti, R. Machiraju, and R. Yagel. Steering image generation with wavelet based perceptual metric. Computer Graphics Forum (Eurographics’ 97), 16(3):241–251, September 1997.
S. Gibson and R.J. Hubbold. Perceptuallydriven radiosity. Computer Graphics Forum, 16(2):129–141,1997.
D.P. Greenberg, K.E. Torrance, P. Shirley, J. Arvo, K.A. Ferwerda, S.N. Pattanaik, E.P.F. Lafortune, B. Walter, S.C. Foo, and B. Trumbore. A framework for realistic image synthesis. In Proc. of Siggraph’97, pages 477–494, 1997.
D. Hedley and A. Worrall and D. Paddon. Selective Culling of Discontinuity Lines. In Dorsey, J. and Slusallek P., editors, Rendering Techniques’ 97, pages 69–80. Springer, 1997.
H. W. Jensen. Global Illumination Using Photon Maps. In X. Pueyo and P. Schroder, editors, Rendering Techniques’ 96, pages 21–30. Springer, 1996.
J.T. Kajiya. The rendering equation. In Proc. of Siggraph’86, pages 143–150, 1986.
B. Li, G.W. Meyer, and R.V. Klassen. A comparison of two images quality models. In Human Vision and Electronic Imageing III, pages 98–109. SPIE Vol. 3299,1998.
D. Lischinski, B. Smits, and D.P. Greenberg. Bounds and error estimates for radiosity. In Proc. of Siggraph’ 94, pages 67–74,1994.
D. Lischinski, F. Tampieri, and D.P. Greenberg. Discontinuity meshing for accurate radiosity. IEEE Computer Graphics and Applications, 12(6):25–39, November 1992.
D. Lischiski, F. Tampieri, and D.P. Greenberg. Combinin hierachical radiosity and discontinuity meshing. In Proc. of Siggraph’93, pages 199–208, 1993.
C. Lloyd and R.J. Beaton. Design of spatialchromatic human vision model for evaluating full.color display systems. In Human Vision and Electronic Imaging: Models, Methodes, and Appl., pages 23–37. SPIE Vol. 1249, 1990.
J. Lubin. A visual discrimination model for imaging system design and development. In Peli. E., editor, Vision models for target detection and recognition, pages 245–283. World Scientific, 1995.
S. Marcelja. Mathematical desscription of the responses of simple cortical cells. Journal of the Optical Society of America, 70:1297–1300, 1980.
W.L. Martens and K. Myszkowski. Psychophysical validation of the Visible Differences Predictor for global illumination applications. In IEEE Visualization’ 98 (Late Breaking Hot Topics), pages 49–52, 1998.
I. Martin, X. Pueyo, and D. Tost. An imagespace refinement criterion for linear hierarchical radiosity. In Graphics Interface’ 97, pages 26–36, 1997.
R.A. Martin, A.J. Ahumada, and J.O. Larimer. Color matrix display sim,ulation based upon luminace and chrominace contrast sensitivity of early vision. In Human Vision, Visual Processing, and Digital Display III, pages 336–342. SPIE Vol. 1666, 1992.
?. Myszkowski. The Visible Differences Predictor: Applications to global illumination problems. In G. Drettakis and N. Max, editors, Rendering Techniques’ 98, pages 223–236. Springer, 1998.
K. Myszkowski and T.L. Kunii. An efficient cluster-based hierarchical progressive radiosity algorithm. In ICSC’ 95, volume 1024 of Lecture Notes in Computer Science, pages 292–303. Springer-Verlag, 1995.
K. Myszkowski anf T.L. Kunii. A case study towards validation of global illumination algorithms: progressive hierarchical radiosity with clustering. The Visual Computer, 16(5):271–288,2000.
K. Myszkowski, A. Wojdala, and K. Wicynski. Non-uniform adaptive meshing for global illumination. Machine Graphics and Vision, 3(4):601–610, 1994.
J. Prikryl and W. Purgathofer. State of the art in perceptually driven radiosity. In State of the Art Reports. Eurographics, 1998.
M. Ramasubramanian, S.N. Pattanaik, and D.P. Greenberg. A perceptually based physical error metric for realistic image synthesis. In Proc. of Siggraph’ 99, pages 73–82, 1999.
H. Rushmeier, G. Ward, C. Piatko, P. Sanders, and B. Rust. Comparing real and synthetic images: some ideas about metrics. In P. Hanrahan W. Purgathofer, editors, Rendering Techninques, 95, pages 82–91. Springer, 1995.
F.X. Sillion and C. Puech. Radiosity and Global Illumination. Morgan Kaufmann, San Francisco, 1994.
C.C. Taylor, Y. Pizlo, J.P. Allebach, and C.A. Bouman. Image quality assessment with a Gabor pyramid model of the Human Visual System. In Human Vision and Electronic Imaging, pages 58–69. SPIE Vol. 3016, 1997.
P.C. Teo and D:J: Heeger. Perceptual iamge distortion. Pages 127–141. SPIE Vol. 2179, 1994.
J. Tumblin and H.E. Rushmeier. Tone reproduction for realistic images. IEEE Computer Graphics and Applications, 13(6):42–48, November 1993.
E. Veach. Robust Monte Carlo methods for lighting simulation. Ph.D. thesis, Stanford University, 1997.
C. Vedel and C. Puech. A testbed for adaptive subdividion in progressive radiosity. In P. Brunet and F.W. Jansen, editors, Photorealistic Rendering in Computer Graphics, 1991.
V. Volevich, K. Myszkowski, A. Khodulev, and Kopylov E.A. Using the Visible Differences Predictor to improve performance of Progressive global illumination computations. ACM Transactions on Graphics, 19(2): 122–161, 2000.
B.J. Walter, P.M. Hubbard, P. Shirley, and D.P. Greenberg. Global illumination using local linear density estimation. ACM Transactions on Graphics, 16(3):217–259, 1997.
A.B. Watson. The Cortex transform: rapid computation of simulated neural images. Comp. Vision Graphics ans Image Processing, 39:311–327, 1987.
S.J.P. Westen, R.L. Lagensijk, and J. Biemond. Perceptual image quality based on a multiple channel HVS model. In Proc. of IEEE Int’l Conference on Acoustics, Speech and Signal Processing, pages 2351–2354, 1995.
H.R. Wilson. Psychophysical models of spatial vision and hyperacuity. In D. Regan, editor, Spatial vision, Vol. 10, Vision and Visual Disfunction, pages 179–206. Cambridge, MA: MIT Press, 1991.
H.R. Wilson and D.J. Gelb. Modified lineelemnt theory for spatial-frequency and width discrimination. Journal of the Optical Society od America, 1(1): 124–131, 1984.
C. Zetzsche and Hauske G. Multiple channel model for the prediction od subjective image quality. In Human Vision, Visual Processing, and Digital Display, pages 209–216. SPIE Vol. 1077, 1989.
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Myszkowski, K. (2002). Perception-Driven Global Illumination and Rendering Computation. In: Sołdek, J., Pejaś, J. (eds) Advanced Computer Systems. The Springer International Series in Engineering and Computer Science, vol 664. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8530-9_22
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DOI: https://doi.org/10.1007/978-1-4419-8530-9_22
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