- freely available
- re-usable
Sensors 2010, 10(1), 775-795; doi:10.3390/s100100775
Review
Statistical Modeling of SAR Images: A Survey
National University of Defence Technology, Changsha 410073, China
Received: 23 November 2009; in revised form: 5 January 2010 / Accepted: 6 January 2010 / Published: 21 January 2010
(This article belongs to the Section Remote Sensors)
Abstract: Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.
Keywords: synthetic aperture radar (SAR) images; statistical models; parameter estimation; probability density function (PDF); the product model
Article Statistics
Click here to load and display the download statistics.Cite This Article
MDPI and ACS Style
Gao, G. Statistical Modeling of SAR Images: A Survey. Sensors 2010, 10, 775-795.
AMA StyleGao G. Statistical Modeling of SAR Images: A Survey. Sensors. 2010; 10(1):775-795.
Chicago/Turabian StyleGao, Gui. 2010. "Statistical Modeling of SAR Images: A Survey." Sensors 10, no. 1: 775-795.
Sensors
EISSN 1424-8220
Published by MDPI Publishing, Basel, Switzerland
RSS
E-Mail Table of Contents Alert
