A model of visual adaptation for realistic image synthesis
作者： James A. Ferwerda , Sumanta N. Pattanaik , Peter Shirley , Donald P. Greenberg
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摘要: In this paper we develop a computational model of visual adaptation for realistic image synthesis based on psychophysical experiments. The captures the changes in threshold visibility, color appearance, acuity, and sensitivity over time that are caused by system’s mechanisms. We use to display results global illumination simulations illuminated at intensities ranging from daylight down starlight. resulting images better capture characteristics scenes viewed wide range levels. Because is data it can be used predict visibility appearance scene features. This allows as basis perceptually-based error metrics limiting precision computations. CR
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