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Generalized Statistical Complexity of SAR Imagery by de Almeida, Eliana S.; de Medeiros, Antonio Carlos; Rosso, Osvaldo A.; Frery, Alejandro C. is a scholarly article available to read on EtoBox.

What is Generalized Statistical Complexity of SAR Imagery about?

A new generalized Statistical Complexity Measure (SCM) was proposed by Rosso et al in 2010. It is a functional that captures the notions of order/disorder and of distance to an equilibrium distribution. The former is computed by a measure of entropy, while the latter depends on the definition of a stochastic divergence. When the scene is illuminated by coherent radiation, image data is corrupted by speckle noise, as is the case of ultrasound-B, sonar, laser and Synthetic Aperture Radar (SAR) sensors. In the amplitude and intensity formats, this noise is multiplicative and non-Gaussian requiring, thus, specialized techniques for image processing and understanding. One of the most successful family of models for describing these images is the Multiplicative Model which leads, among other probability distributions, to the G0 law. This distribution has been validated in the literature as an expressive and tractable model, deserving the "universal" denomination for its ability to describe most types of targets. In order to compute the statistical complexity of a site in an image corrupted by speckle noise, we assume that the equilibrium distribution is that of fully developed speckle, n

Author

de Almeida, Eliana S.; de Medeiros, Antonio Carlos; Rosso, Osvaldo A.; Frery, Alejandro C.

Published

2012

Language

EN