Parameter estimation in SAR imagery using stochastic distances and asymmetric kernels
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Institute of Electrical and Electronics Engineers Inc.
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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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Gambini, María Juliana, et al., 2015. Parameter estimation in SAR imagery using stochastic distances and asymmetric kernels. IEEE Journal of selected topics in applied earth observations and remote sensing. New York: Institute of Electrical and Electronics Engineers Inc., vol. 8, no. 1, p. 365-375. ISSN 1939-1404.
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