Providing a New Approach for Modeling and Parameter Estimation of Probability Density Function of Noise in Digital Images

dc.creatorYaghoobi, Hanif
dc.creatorMaghooli, Keivan
dc.creatorBarandagh, Alireza Ghahramani
dc.date2015-12-19
dc.date.accessioned2023-09-27T19:28:23Z
dc.date.available2023-09-27T19:28:23Z
dc.identifierhttps://periodicos.ufsm.br/cienciaenatura/article/view/20770
dc.identifier10.5902/2179460X20770
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8938733
dc.descriptionThe main part of the noise in digital images arises when taking pictures or transmission. There is noise in the imagescaptured by the image sensors of the real world. Noise, based on its causes can have different probability density functions.For example, such a model is called the Poisson distribution function of the random nature of photon arrival process that isconsistent with the distribution of pixel values measured. The parameters of the noise probability density function (PDF)can be achieved to some extent the properties of the sensor. But, we need to estimate the parameters for imaging settings. Ifwe assume that the PDF of noise is approximately Gaussian, then we need only to estimate the mean and variance becausethe Gaussian PDF with only two parameters is determined. In fact, in many cases, PDF of noise is not Gaussian and it hasunknown distribution. In this study, we introduce a generalized probability density function for modeling noise in imagesand propose a method to estimate its parameters. Because the generalized probability density function has multipleparameters, so use common parameter estimation techniques such as derivative method to maximize the likelihood functionwould be extremely difficult. In this study, we propose the use of evolutionary algorithms for global optimization. Theresults show that this method accurately estimates the probability density function parameters.en-US
dc.formatapplication/pdf
dc.languagepor
dc.publisherUniversidade Federal de Santa Mariaen-US
dc.relationhttps://periodicos.ufsm.br/cienciaenatura/article/view/20770/pdf
dc.sourceCiência e Natura; Vol. 37 (2015): SPECIAL EDITION - PART 2; 182-189en-US
dc.sourceCiência e Natura; v. 37 (2015): EDIÇÃO ESPECIAL – PART 2; 182-189pt-BR
dc.source2179-460X
dc.source0100-8307
dc.titleProviding a New Approach for Modeling and Parameter Estimation of Probability Density Function of Noise in Digital Imagesen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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