Modeling Quantized Coefficients with Generalized Gaussian Distribution with Exponent 1 / m, \(m=2,3,\ldots \)

  • Robert KrupińskiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 659)


The different types of signals in the image and signal processing applications can be modeled with generalized Gaussian distribution (GGD). When limiting to the special cases, then the closed form equations can be determined. The special cases with the exponents \(p=2\) (Gaussian distribution), \(p=1\) (Laplacian distribution), \(p=1/2\) and \(p=1/3\) are considered in literature. In the article, more general approach for the exponents 1 / m, \(m=2,3,\ldots \) is analyzed, which are related to the peaky shapes of GGD. The maximum likelihood method for a discrete random variable is derived for this subclass of distributions.


Estimation Generalized Gaussian distribution Maximum likelihood method Centroid reconstruction 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Chair of Signal Processing and Multimedia EngineeringWest-Pomeranian University of Technology in SzczecinSzczecinPoland

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