Asymmetric Generalized Gaussian DistributionParameters Estimation based on MaximumLikelihood, Moments and Entropy

Type : Article de conférence
Auteur(s) :  Nafaa Nacereddine, Aicha Baya Goumeidane
Année :  2019
Domaine : Electronique
Conférence: 15th IEEE International Conference on Intelligent Computer Communication and Processing
Lieu de la conférence:  Cluj-Napoca, Romania
Résumé en PDF :  (résumé en pdf)
Fulltext en PDF :  (.pdf)
Mots clés :  Asymmetric generalized Gaussian distribution, Parameter estimation, maximum likelihood, Moments, Entropy.

Résumé : 

In this paper, we address the problem of estimatingthe parameters of Asymmetric Generalized Gaussian Distribution(AGGD) using three estimation mehods, namely, Maximum LikelihoodEstimation (MLE), Moment Matching Estimation (MME)and Entropy Matching Estimaion (EME). For this purpose, thesemethods are applied on an unimodal histogram fitting of animage corrupted with AGGD noise. Experiments show that theeffectiveness of each method comparatively to the other onedepends on the variation range of the shape factor.