A Fast Parallel Algorithm for Blind Estimation of Noise Variance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-dimensional signal and image processing
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Fundamentals of statistical signal processing: estimation theory
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CCIW'11 Proceedings of the Third international conference on Computational color imaging
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PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Robust Noise Estimation Based on Noise Injection
Journal of Signal Processing Systems
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In this paper, we focus on the problem of automatic noise parameter estimation for additive and multiplicative models and propose a simple and novel method to this end. Specifically we show that if the image to work with has a sufficiently great amount of low-variability areas (which turns out to be a typical feature in most images), the variance of noise (if additive) can be estimated as the mode of the distribution of local variances in the image and the coefficient of variation of noise (if multiplicative) can be estimated as the mode of the distribution of local estimates of the coefficient of variation. Additionally, a model for the sample variance distribution for an image plus noise is proposed and studied. Experiments show the goodness of the proposed method, specially in recursive or iterative filtering methods.