Multidimensional Speckle Noise Model
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tidimensional Speckle Noise Model ´ Carlos Lopez-Mart´ ınez Equipe SAPHIR, Institut d’Electronique et de T´el´ecommunications de Rennes UMR CNRS 6164, Universit´e de Rennes 1, Campus de Beaulieu, Building 11D, Room 101, 263 Avenue General Leclerc, 35042 Rennes Cedex, France Email: [email protected]
` Xavier Fabregas Grup de Teledeteccio Activa, Departament de Teoria del Senyal i Communicacions, Universitat Politecnica de Catalunya (UPC), Campus Nord, Building D3, Room 118, Calle Jordi Girona 1-3, 08034 Barcelona, Spain Email: [email protected]
Eric Pottier Equipe SAPHIR, Institut d’Electronique et de T´el´ecommunications de Rennes UMR CNRS 6164, Universit´e de Rennes 1, Campus de Beaulieu, Building 11D, Room 101, 263 Avenue General Leclerc, 35042 Rennes Cedex, France Email: [email protected] Received 30 June 2004; Revised 23 November 2004 One of the main problems of SAR imagery is the presence of speckle noise, originated by the inherent coherent nature of this type of systems. For one-dimensional SAR systems it has been demonstrated that speckle can be considered as a multiplicative noise term. Nevertheless, this simple model cannot be exported when multidimensional SAR imagery is addressed. This paper is devoted to present the latest advances into the definition of a multidimensional speckle noise model which does not depend on the data dimensionality. Speckle noise may be modeled by multiplicative and additive noise sources, whose combination is determined by the data’s correlation structure. The validity of the proposed model is demonstrated by its application to a real L-band multidimensional SAR dataset acquired by the German ESAR sensor. Keywords and phrases: multidimensional SAR imagery, speckle noise, noise modeling.
1.
INTRODUCTION
Synthetic aperture radar (SAR) has become a well established, active, microwave imaging technique capable of monitoring, and characterizing, the surface of the Earth as well as its dynamics. In a first period, one-dimensional SAR systems allowed to demonstrate the capacities of this technology to provide information about the Earth surface reflectivity with a high spatial resolution, independently of the weather conditions or the day-night cycle [1]. But, the availability of multidimensional SAR systems which occurred in the last decade has been the fact which has really boosted the interest of the remote sensing community in these systems [2]. Multidimensional SAR systems open the possibility to increase the quantity of information which can be gathered from the scene under observation, and therefore, to better characterize it in a quantitative way. The additional This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
information that multichannel data sets provide arises through the increased parameter space of the acquisitions as well as the correlation structure between the channels. The a
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