Averaging of adjacent samples is very useful in polarimetric radar data analysis. It has a similar effect as look summation in single-polarization SAR processing. It reduces the "noisy" effects of speckle, but at the expense of degrading the resolution of the image , . When values in the neighbourhood of a sample are averaged, scatterers that were once represented by distinct samples become consolidated in the image.
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When the scattering matrix of a single pixel is measured by the radar system, there are not enough degrees of freedom to represent noise as well as the target's scattering properties, even though noise is present in the observation. For this reason, a single scatterer is assumed even though there may be multiple scattering mechanisms and noise present in the pixel. However, when converted to a power representation and neighbouring samples are averaged, a composite pixel is obtained in which the noise and different scattering mechanisms can be explicitly represented.
Averaging is performed in the power domain, because the energy of individual components is preserved in power representations (energy is not preserved when averaging in the "voltage" domain). Usually the Stokes, covariance or coherency matrix representations are used for the averaging. The averaging is usually performed as a post-processing operation, by averaging the power matrix values of adjacent samples. Averaging has the additional advantages of reducing the data volume, and can be used to create equal pixel spacing in ground range and in azimuth.
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