Zinno, Ivana (2011) Fractal Models for SAR images. [Tesi di dottorato] (Unpublished)

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Item Type: Tesi di dottorato
Lingua: English
Title: Fractal Models for SAR images
Creators:
CreatorsEmail
Zinno, Ivanaivana.zinno@fastwebnet.it
Date: 30 November 2011
Number of Pages: 145
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria biomedica, elettronica e delle comunicazioni
Scuola di dottorato: Ingegneria dell'informazione
Dottorato: Ingegneria elettronica e delle telecomunicazioni
Ciclo di dottorato: 24
Coordinatore del Corso di dottorato:
nomeemail
Rinaldi, Niccolònirinald@unina.it
Tutor:
nomeemail
Daniele, Ricciodariccio@unina.it
Date: 30 November 2011
Number of Pages: 145
Uncontrolled Keywords: Synthetic Aperture Radar, fractals, radar imaging
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/02 - Campi elettromagnetici
Date Deposited: 07 Dec 2011 12:21
Last Modified: 30 Apr 2014 19:49
URI: http://www.fedoa.unina.it/id/eprint/8946
DOI: 10.6092/UNINA/FEDOA/8946

Abstract

In this thesis the modeling of SAR (Synthetic Aperture Radar) images of natural surfaces described via fractal models is dealt with. A complete theoretical forward model linking the parameters describing the scene observed by the sensor to the stochastic characterization of the relevant SAR image is provided. The inverse problem is treated as well: a SAR image post-processing able to automatically retrieve - operating on an amplitude single SAR image - the fractal parameters of the scene, is presented. The developed imaging model is based on sound geometrical and electromagnetic models that are combined according to the SAR impulse response function. The power spectral densities of appropriate cuts of the SAR image are evaluated in closed form in terms of the surface fractal parameters. The theoretical results are here conceptually assessed, analytically derived, graphically validated and numerically verified. Moreover, based on the inversion of the forward theoretical model, an innovative SAR image post-processing for the fractal parameters estimation is implemented. It is firstly tested on simulated SAR images, then it is applied to different types of new generation (i.e. high resolution) SAR images. The generated fractal maps show themselves to be very useful for a wide range of application, e.g. prevention and monitoring of environmental disasters, geodynamic processes interpretation, land classification, rural planning, and so on.

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