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Multifrequency SAR polarimetric noise model validation

Carlos López-Martínez (1)

(1) Technical University of Catalonia (UPC), Jordi Girona, 1-3, Campus Nord, Edifici D3-118, E-08034, Barcelona, Spain


SAR polarimetry is a well-established technique to gather information about the earth’s surface. Most of the earth’s surface scatterers can be considered as distributed scatterers, being modelled as a set of randomly located point scatterers. When a SAR system illuminates such a scatterer, the recovered complex signal can be modelled as the coherent addition of the scattered signals by each one of the point scatterers. The main consequence of this coherent nature is that the recovered signal is affected by speckle. Despite speckle is a deterministic effect, due to the complexity involved within the scattering process it can be only statistically analysed. Therefore, speckle is considered as a source of noise. The speckle problem has been already solved for the case of single-channel SAR systems. The speckle can be considered as a multiplicative noise term for the amplitude and additive for the phase. For the case of multi-channel SAR systems as a polarimetric SAR systems, the speckle problem is more complex due to the fact that the SAR channels present a non-zero correlation, which also contains information about the scattering process. In a general case, polarimetric SAR data are described by the covariance matrix. Recently, the authors presented, by the first time, a speckle noise model for all the elements of the covariance matrix. In this paper, the authors will present a validation of this new polarimetric speckle noise model for three SAR polarimetric datasets in L- C- and P-band. The aim of this paper is to show the validity of the noise model for all the frequency range and to show possible frequency effects within this noise model. The paper shall be divided in two parts. A short presentation on the polarimetric speckle noise model shall be given. The second part shall be devoted to present the study of the polarimetric speckle noise model for all the three datasets. Finally, some conclusion shall be presented.


Full paper

Full paper


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