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<title>Spatial phase behavior in SAR images</title>
Author(s) -
David Petit,
Loïc Soucille,
JeanDenis Durou,
F. Adragna,
Hélène Oriot,
Élisabeth Simonetto
Publication year - 2002
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.453977
Subject(s) - estimator , computer science , phase (matter) , amplitude , image resolution , synthetic aperture radar , correlation , sampling (signal processing) , spatial correlation , algorithm , set (abstract data type) , image (mathematics) , data set , pattern recognition (psychology) , artificial intelligence , mathematics , computer vision , statistics , optics , physics , telecommunications , geometry , filter (signal processing) , quantum mechanics , programming language
It is well known that a SAR image is composed of two types of information: amplitude and phase. Nevertheless, the information contained in the phase is hardly exploited on its own. Indeed, the number of processes at work and the scale difference between the image resolution and the wavelength induce, with regard to the phase, a quasi-random spatial behavior. However, our recent work shows that the phase of one image can be spatially correlated. First, we define an estimator for the spatial correlation of the phase, and study its behavior with real data. We assess the phase correlation according to the resolution and the type of surface. Then, we set down the theoretical bases of a statistical model of this behavior. We highlight the conditions required with regard to the resolution, the sampling rate, and the impulse response. We therefore identify the best kinds of surfaces, so that the phenomenon occurs. Hence, we simulate the phase correlation for different cases according to the phase model defined. We choose suitable parameters to the conditions of the real data and compare measurements and simulations. Finally, we propose possible applications related to the use of this new source of information.

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