Abstract:This paper proposes a reduced reference quality assessment model based on spiking neural network (SNN) in order to predict which image highlights perceptual noise in unbiased global illumination algorithms. These algorithms provide photo-realistic images by increasing the number of paths as proved by Monte Carlo theory. The objective is to find the number of paths that are required in order to ensure that most of the observers cannot perceive noise in any part of the image. A comparative study of this model wi… Show more
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