Polarimetric SAR speckle noise model

• Published in: IEEE transactions on geoscience and remote sensing Vol. 41; no. 10; pp. 2232 - 2242
• Main Authors: Lopez-Martinez, C., Fabregas, X.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY IEEE 01.10.2003; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); IEEE Institute Electrical Electronics Engineers INC
• Subjects: Applied geophysics; Coherence; Correlation; Covariance matrix; Diversity reception; Earth sciences; Earth, ocean, space; Enginyeria de la telecomunicació; Exact sciences and technology; Internal geophysics; Mathematical models; Multidimensional data; Multidimensional systems; Noise; Parameter estimation; Polarization; Radar polarimetry; Remote monitoring; SAR; SAR (Synthetic Aperture Radar); Senyal, Teoria del (Telecomunicació); Signal theory (Telecommunication); Spatial resolution; Speckle; Speckle noise model; Synthetic aperture radar; Àrees temàtiques de la UPC; models; synthetic aperture radar; speckle noise; correlation; noise; noise modeling; remote sensing; covariance; polarization; Covariance matrix; synthetic aperture radar (SAR) polarimetry
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2003.815240

Synthetic aperture radar (SAR) data are affected by speckle noise, originated by the SAR system's coherent nature. The problem of speckle noise in one-dimensional (1-D) data is already solved, as speckle has a multiplicative characteristic. SAR polarimetry represents an extension to multidimensional data by the use of polarization wave diversity. As a consequence of the existence of a correlation degree between the SAR images, the 1-D speckle noise model cannot be extended to multidimensional SAR data. This paper is devoted to present a completely new speckle noise model for the complex covariance matrix describing polarimetric SAR data in the distributed scatterers case. As is shown, this new model is able to identify which are the noise mechanisms in all the covariance matrix elements. The speckle noise model is validated by using real L-band polarimetric data acquired with the German E-SAR sensor.