Parameter estimation in SAR imagery using stochastic distances and asymmetric kernels
Fecha
2015-01Autor
Gambini, María Juliana
Cassetti, Julia Analía
Lucini, María Magdalena
Frery, Alejandro César
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The Statistical modeling of the data is essential in order to interpret synthetic aperture radar (SAR) images. Speckled data have been described under the multiplicative model using the G family of distributions, which is able to describe rough and extremely rough areas better than the K distribution. The survey article discusses in detail several statistical models for this kind of data. Under the G model, different degrees of roughness are associated with different parameter values; therefore, it is of paramount importance to have high quality estimators. Several works have been devoted to the subject of improving estimation with two main venues of research, namely, analytic and resampling procedures.
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