Visual Equivalence: Towards a New Standard for Image Fidelity
Ganesh Ramanarayanan, James Ferwerda, Bruce Walter and Kavita Bala
Proceedings of SIGGRAPH 2007 (SIGGRAPH 2007, ACM Transactions on Graphics, Volume 26, Number 3)
Abstract:
Efficient, realistic rendering
of complex scenes is one of the grand challenges in computer graphics.
Perceptually based rendering addresses this challenge by taking
advantage of the limits of human vision. However, existing methods,
based on predicting visible image differences, are too conservative
because some kinds of image differences do not matter to human
observers. In this paper, we introduce the concept of visual
equivalence, a new standard for image fidelity in graphics. Images are
visually equivalent if they convey the same impressions of scene
appearance, even if they are visibly different. To understand this
phenomenon, we conduct a series of experiments that explore how object
geometry, material, and illumination interact to provide information
about appearance, and we characterize how two kinds of transformations
on illumination maps (blurring and warping) affect these appearance
attributes. We then derive visual equivalence predictors (VEPs):
metrics for predicting when images rendered with transformed
illumination maps will be visually equivalent to images rendered with
reference maps. We also run a confirmatory study to validate the
effectiveness of these VEPs for general scenes. Finally, we show how
VEPs can be used to improve the efficiency of two rendering algorithms:
Lightcuts and precomputed radiance transfer. This work represents some
promising first steps towards developing perceptual metrics based on
higher order aspects of visual coding.
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Acknowledgments: National Science Foundation (NSF),
Intel Corporation.