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Progress In Electromagnetics Research
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MODELING SAR IMAGES BASED ON A GENERALIZED GAMMA DISTRIBUTION FOR TEXTURE COMPONENT

By G. Gao, X. Qin, and S. Zhou

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Abstract:
In the applications of synthetic aperture radar (SAR) data, a crucial problem is to develop precise models for the statistics of the pixel amplitudes or intensities. In this paper, a new statistical model, called simply here GΓΓ, is proposed based on the product model by assuming the radar cross section (RCS) components (texture components) of the return obey a recently empirical generalized Gamma distribution. Meanwhile, we demonstrate theoretically that the proposed GΓΓ model has the well-known K and g0 distributions as special cases. We also derived analytically the estimators of the presented GΓΓ model by applying the "method-of-log-cumulants" (MoLC). Finally, the performance of the proposed model is tested by using some measured SAR images.

Citation:
G. Gao, X. Qin, and S. Zhou, "Modeling SAR Images Based on a Generalized Gamma Distribution for Texture Component," Progress In Electromagnetics Research, Vol. 137, 669-685, 2013.
doi:10.2528/PIER13011807
http://www.jpier.org/PIER/pier.php?paper=13011807

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