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Statistical modeling of polarimetric SAR data: a survey and challenges

Author
Deng, X.; Lopez, C.; Chen, J.; Han, P.
Type of activity
Journal article
Journal
Remote sensing
Date of publication
2017-04-01
Volume
9
First page
1
Last page
34
DOI
https://doi.org/10.3390/rs9040348 Open in new window
Repository
http://hdl.handle.net/2117/104285 Open in new window
URL
http://www.mdpi.com/2072-4292/9/4/348 Open in new window
Abstract
Knowledge of the exact statistical properties of the signal plays an important role in the applications of Polarimetric Synthetic Aperture Radar (PolSAR) data. In the last three decades, a considerable research effort has been devoted to finding accurate statistical models for PolSAR data, and a number of distributions have been proposed. In order to see the differences of various models and to make a comparison among them, a survey is provided in this paper. Texture models, which could capture ...
Citation
Deng, X., Lopez, C., Chen, J., Han, P. Statistical modeling of polarimetric SAR data: a survey and challenges. "Remote sensing", 1 Abril 2017, vol. 9, p. 1-34.
Keywords
Copulas, Finite mixture models, Polarimetric SAR, Statistical modeling, Texture models
Group of research
RSLAB - Remote Sensing Lab

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