Perceptual illumination components: a new approach to efficient, high quality global illumination rendering

In this paper we introduce a new perceptual metric for efficient, high quality, global illumination rendering. The metric is based on a rendering-by-components framework in which the direct, and indirect diffuse, glossy, and specular light transport paths are separately computed and then composited to produce an image. The metric predicts the perceptual importances of the computationally expensive indirect illumination components with respect to image quality. To develop the metric we conducted a series of psychophysical experiments in which we measured and modeled the perceptual importances of the components. An important property of this new metric is that it predicts component importances from inexpensive estimates of the reflectance properties of a scene, and therefore adds negligible overhead to the rendering process. This perceptual metric should enable the development of an important new class of efficient global-illumination rendering systems that can intelligently allocate limited computational resources, to provide high quality images at interactive rates.

[1]  H. B. Barlow,et al.  What does the eye see best? , 1983, Nature.

[2]  J P Thomas,et al.  Independent processing of suprathreshold spatial gratings as a function of their separation in spatial frequency. , 1989, Journal of the Optical Society of America. A, Optics and image science.

[3]  G. Sandini,et al.  The Role of High Spatial Frequencies in Face Perception , 1983, Perception.

[4]  James F. Blinn,et al.  Models of light reflection for computer synthesized pictures , 1977, SIGGRAPH.

[5]  Donald P. Greenberg,et al.  Spatiotemporal sensitivity and visual attention for efficient rendering of dynamic environments , 2001, TOGS.

[6]  R. F. Hess,et al.  Evidence for spatially local computations underlying discrimination of periodic patterns in fovea and periphery , 1987, Vision Research.

[7]  P GreenbergDonald,et al.  Interactive global illumination in dynamic scenes , 2002 .

[8]  Donald P. Greenberg,et al.  Global illumination using local linear density estimation , 1997, TOGS.

[9]  Yehoshua Y. Zeevi,et al.  Adaptive Two-Dimensional Neighborhood Sensitivity Control By A One-Dimensional Process , 1988, Other Conferences.

[10]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[11]  J. Briers,et al.  Retinal blood-flow visualization by means of laser speckle photography. , 1982, Investigative ophthalmology & visual science.

[12]  M. Cannon,et al.  Perceived contrast and stimulus size: Experiment and simulation , 1988, Vision Research.

[13]  G. Sperling,et al.  Limits of visual communication: the effect of signal-to-noise ratio on the intelligibility of American Sign Language. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[14]  M. Georgeson,et al.  Contrast constancy: deblurring in human vision by spatial frequency channels. , 1975, The Journal of physiology.

[15]  R. Sekuler,et al.  Assessing spatial vision of older people. , 1982, American journal of optometry and physiological optics.

[16]  C. Enroth-Cugell,et al.  Chapter 9 Visual adaptation and retinal gain controls , 1984 .

[17]  Eric L. Schwartz,et al.  Computer-Aided Neuroanatomy: Differential Geometry of Cortical Surfaces and an Optimal Flattening Algorithm , 1986, IEEE Computer Graphics and Applications.

[18]  Yehoshua Y. Zeevi,et al.  Pyramidal Image Representation In Nonuniform Systems , 1988, Other Conferences.

[19]  D. H. Kelly.  Visual Contrast Sensitivity , 1977 .

[20]  Joseph L. Zinnes,et al.  Theory and Methods of Scaling. , 1958 .

[21]  I Rentschler,et al.  Hidden-face recognition: comparing foveal and extrafoveal performance. , 1985, Human neurobiology.

[22]  Arthur P Ginsburg,et al.  Visual Information Processing Based on Spatial Filters Constrained by Biological Data. , 1978 .

[23]  G. Lennerstrand,et al.  PICTURE SIMULATION OF CONTRAST SENSITIVITY IN ORGANIC AND FUNCTIONAL AMBLYOPIA , 1981, Acta ophthalmologica.

[24]  Gary W. Meyer,et al.  Color spatial acuity control of a screen subdivision image synthesis algorithm , 1992, Electronic Imaging.

[25]  Raghu Machiraju,et al.  Steering Image Generation with Wavelet Based Perceptual Metric , 1997, Comput. Graph. Forum.

[26]  Gary W. Meyer,et al.  A frequency based ray tracer , 1995, SIGGRAPH.

[27]  G. Legge,et al.  Psychophysics of reading. VI—The role of contrast in low vision , 1989, Vision Research.

[28]  Werner Purgathofer,et al.  Importance-Driven Hierarchical Stochastic Ray Radiosity , 2000, WSCG.

[29]  Derek J. Paddon,et al.  Selective Culling of Discontinuity Lines , 1997, Rendering Techniques.

[30]  Joel Pokorny,et al.  Sawtooth contrast sensitivity: Decrements have the edge , 1989, Vision Research.

[31]  M. Cannon,et al.  Perceived contrast in the fovea and periphery. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[32]  D. Burr,et al.  Feature detection in human vision: a phase-dependent energy model , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[33]  Gregory J. Ward,et al.  Measuring and modeling anisotropic reflection , 1992, SIGGRAPH.

[34]  Gordon E. Legge,et al.  Psychophysics of reading—II. Low vision , 1985, Vision Research.

[35]  Karol Myszkowski,et al.  The Visible Differences Predictor: Applications to Global Illumination Problems , 1998, Rendering Techniques.

[36]  Eric L. Schwartz,et al.  Applications of computer graphics and image processing to 2D and 3D modeling of the functional architecture of visual cortex , 1988, IEEE Computer Graphics and Applications.

[37]  Eli Peli,et al.  Image Enhancement For The Visually Impaired , 1984 .

[38]  D. G. Albrecht,et al.  Spatial frequency selectivity of cells in macaque visual cortex , 1982, Vision Research.

[39]  Henrik Wann Jensen,et al.  Adaptive Smpling and Bias Estimation in Path Tracing , 1997, Rendering Techniques.

[40]  Charles A. Poynton,et al.  A technical introduction to digital video , 1996 .

[41]  A B Watson,et al.  Efficiency of a model human image code. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[42]  E. Peli.  Contrast in complex images. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[43]  S. Klein,et al.  Evidence against narrow-band spatial frequency channels in human vision: the detectability of frequency modulated gratings , 1975, Vision Research.

[44]  D. Badcock.  Spatial phase or luminance profile discrimination? , 1984, Vision Research.

[45]  Roger J. Hubbold,et al.  Perceptually‐Driven Radiosity , 1997, Comput. Graph. Forum.

[46]  R. Sekuler,et al.  Aging and low-contrast vision: face perception. , 1981, Investigative ophthalmology & visual science.

[47]  Hans-Peter Seidel,et al.  Perceptually Guided Corrective Splatting , 2001, Comput. Graph. Forum.

[48]  Peter Shirley,et al.  A ray tracing method for illumination calculation in diffuse-specular scenes , 1990 .

[49]  Donald P. Greenberg,et al.  Toward a psychophysically-based light reflection model for image synthesis , 2000, SIGGRAPH.

[50]  Donald P. Greenberg,et al.  Interactive global illumination in dynamic scenes , 2002, SIGGRAPH.

[51]  Donald P. Greenberg,et al.  Using Perceptual Texture Masking for Efficient Image Synthesis , 2002, Comput. Graph. Forum.

[52]  Gary W. Meyer,et al.  A perceptually based adaptive sampling algorithm , 1998, SIGGRAPH.

[53]  G. Sperling,et al.  Spatial-frequency bands in complex visual stimuli: American Sign Language. , 1988, Journal of the Optical Society of America. A, Optics and image science.

[54]  Gerald Westheimer.  The oscilloscopic view: Retinal illuminance and contrast of point and line targets , 1985, Vision Research.

[55]  Eli Peli,et al.  Contrast In Images , 1988, Other Conferences.

[56]  Karol Myszkowski,et al.  Perception-Based Fast Rendering and Antialiasing of Walkthrough Sequences , 2000, IEEE Trans. Vis. Comput. Graph..

[57]  R. F. Hess,et al.  The contrast sensitivity gradient across the human visual field: With emphasis on the low spatial frequency range , 1989, Vision Research.

[58]  Donald P. Greenberg,et al.  A perceptually based physical error metric for realistic image synthesis , 1999, SIGGRAPH.

[59]  Hans-Peter Seidel,et al.  Perception-guided global illumination solution for animation rendering , 2001, SIGGRAPH.

[60]  Fabio Pellacini,et al.  Perceptually-driven decision theory for interactive realistic rendering , 2003, TOGS.

[61]  Don P. Mitchell,et al.  Generating antialiased images at low sampling densities , 1987, SIGGRAPH.

[62]  László Neumann,et al.  Perception Based Color Image Difference , 1998, Comput. Graph. Forum.

[63]  T. B. Lawton.  Improved word recognition for observers with age-related maculopathies using compensation filters , 1988 .

[64]  Roger J. Hubbold,et al.  A Perceptually-Driven Parallel Algorithm for Efficient Radiosity Simulation , 2000, IEEE Trans. Vis. Comput. Graph..

[65]  F BlinnJames.  Models of light reflection for computer synthesized pictures , 1977 .