Analysis of a physically realistic film grain model, and a Gaussian film grain synthesis algorithm

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Abstract

Film grain is a highly valued characteristic of analog images, thus realistic digital film grain synthesis is an important objective for many modern photographers and film-makers. We carry out a theoretical analysis of a physically realistic film grain model, based on a Boolean model, and derive expressions for the expected value and covariance of the film grain texture. We approximate these quantities using a Monte Carlo simulation, and use them to propose a film grain synthesis algorithm based on Gaussian textures. With numerical and visual experiments, we demonstrate the correctness and subjective qualities of the proposed algorithm.

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Newson, A., Faraj, N., Delon, J., & Galerne, B. (2017). Analysis of a physically realistic film grain model, and a Gaussian film grain synthesis algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10302 LNCS, pp. 196–207). Springer Verlag. https://doi.org/10.1007/978-3-319-58771-4_16

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