Performance of spectral estimators in simulated synthetic aperture radar images

The spectral density is an important quantifier of the texture that, in tur n, can be related to biophysical magnitudes. In this manner, it can be used to establish the kind of target being under observation. Some estimators f or the spectral density of the return in Synthetic Aperture Radar (SAR) ima ges are studied using Monte Carlo experiences. These SAR images are contami nated by a particular kind of noise, called speckle, that does not obey the classical hypothesis of being Gaussian and of entering the signal in an ad ditive manner requiring, thus, a careful treatment. There art: two approach es to the problem of the presence of speckle noise, one being the use of te chniques for its reduction (using specially devised filters) and the other the proposal of methodologies that take its presence into account. Both app roaches will be used here, to the problem of estimating the spatial correla tion structure of the ground truth under the presence of speckle noise. The performance of these estimators will be assessed using Monte Carlo experie nces, since the problem is analytically intractable.