Mimick capacity of Generalized Gamma distribution for high resolution SAR image statistical modeling

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Abstract

In this paper we investigate the capacity of the Generalized Gamma distribution to mimick (or imitate) thanks to its three parameters other useful SAR distributions. We first compare it with the Fisher distribution when mimicking a K distribution of reference, thanks to the log-cumulant approach and through a Kullback-Leibler divergence. We then study how the Generalized Gamma distribution can imitate a Log-Normal distribution as asymtotic limit.

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6328-6331
Number of pages4
ISBN (Electronic)9781509033324
DOIs
Publication statusPublished - 1 Nov 2016
Externally publishedYes
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/TerritoryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • Generalized Gamma distribution
  • Statistical modeling of SAR data
  • log-cumulant parameter estimation

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