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Article Dans Une Revue Signal Processing Année : 2015

Generalized signal-dependent noise model and parameter estimation for natural images

Résumé

The goal of this paper is to propose a generalized signal-dependent noise model that is more appropriate to describe a natural image acquired by a digital camera than the conventional Additive White Gaussian Noise model widely used in image processing. This non-linear noise model takes into account effects in the image acquisition pipeline of a digital camera. In this paper, an algorithm for estimation of noise model parameters from a single image is designed. Then the proposed noise model is applied with the Local Linear Minimum Mean Square Error filter to design an efficient image denoising method.
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Dates et versions

hal-01915653 , version 1 (19-03-2019)

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Thanh Hai Thai, Florent Retraint, Rémi Cogranne. Generalized signal-dependent noise model and parameter estimation for natural images. Signal Processing, 2015, 114, pp.164-170. ⟨10.1016/j.sigpro.2015.02.020⟩. ⟨hal-01915653⟩
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