An Evaluation Method of SAR Images Based on Kullback-Leiber Divergence

被引：1

作者：

Hu, LiPing ^{[1
]}

Wang, Chao ^{[1
]}

机构：

[1] Sci & Technol Electromagnet Scattering Lab, Beijing, Peoples R China

来源：

IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS | 2015年

关键词：

quantitiveevalution; Kullback-Leiber (KL); KK distribution; moving and stationary target recognition (MSTAR); synthetic aperture radar (SAR); ATR;

D O I：

10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.293

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A quantitative evaluation method of synthetic aperture radar (SAR) simulation image based on the KK distribution and the Kullback-Leiber (KL) divergence is introduced in order to evaluate the validity of SAR templates by theoretical modeling. Firstly, the histogram of SAR image is modeled with the KK distribution. And then, the symmetric KL distance between two probability distributions is defined. By computing the KL distances between the simulated SAR images and the moving and stationary target recognition (MSTAR) SAR images of three typical ground vehicles (BMP2, BTR70, and T72), we conclude that the evaluation method based on the Kullback-Leiber divergence is effective.

引用

页码：1611 / 1616

页数：6

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