performance of spectral estimators in simulated synthetic aperture radar images

摘要

The spectral density is an important quantifier of the texture that,in turn,can be related to biophysical amgnitudes.In this manner,it can be used to establish the kind of target being under observation.Some estimators for the spectral density of the return in Synthetic Aperture Radar (SAR) images are studied using Monte Carlo experiences.These SAR images are contaminated by a particular kind of noise,called speckle,that does not obey the classical hypothesis of being Gaussian and of entering the dignal in an additive manner requiring,thus,a careful treatment.There are two approaches to the problem of the presence of speckle noise,one being the use of techniques for its reduction (using specially devised filters) and the other the proposal of mehtodologies that take its presence into account.Both approaches will be used here,to the problem of estimating the spatial correlation structure of the ground truth under the presence of speckle noise.The performance of these estimators will be assessed using Monte Carlo Experiences,since the problem is analytically intractable.