Sampling from the 𝒢I0 distribution

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2018-12
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Chan, Debora
Rey, Andrea
Gambini, Juliana
Frery, Alejandro C.
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"Synthetic Aperture Radar (SAR) images are widely used in several environmental applications because they provide information which cannot be obtained with other sensors. The 𝒢I0 distribution is an important model for these images because of its flexibility (it provides a suitable way for modeling areas with different degrees of texture, reflectivity and signal-to-noise ratio) and tractability (it is closely related to the Snedekor-F, Pareto Type II, and Gamma distributions). Simulated data are important for devising tools for SAR image processing, analysis and interpretation, among other applications. We compare four ways for sampling data that follow the 𝒢I0 distribution, using several criteria for assessing the quality of the generated data and the consumed processing time. The experiments are performed running codes in four different programming languages. The experimental results indicate that although there is no overall best method in all the considered programming languages, it is possible to make specific recommendations for each one."
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