Statistical Modeling of SAR Images: A Survey

被引：198
作者：
Gao, Gui [1 ]
机构：
[1] Natl Univ Def Technol, Changsha 410073, Hunan, Peoples R China
来源：
SENSORS | 2010年 / 10卷 / 01期
关键词：
synthetic aperture radar (SAR) images; statistical models; parameter estimation; probability density function (PDF); the product model; RADAR CLUTTER; PHASE STATISTICS; TARGET DETECTION; K-DISTRIBUTION; CLASSIFICATION; SEGMENTATION; APERTURE; DISTRIBUTIONS; INFORMATION; PARAMETERS;
D O I：
10.3390/s100100775
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
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.
引用
收藏
页码：775 / 795
页数：21
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