一种基于小波变换的SAR图像船舰检测的新算法

陈德元; 凃国防

doi:10.3724/SP.J.1146.2005.01089

一种基于小波变换的SAR图像船舰检测的新算法

doi: 10.3724/SP.J.1146.2005.01089

陈德元^{①②;凃国防},
凃国防

基金项目:

国家十五攻关项目(k2004060420)和国家自然科学基金(90304003)资助课题

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- 文章访问数: 3335
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- 被引次数: 0
出版历程
- 收稿日期: 2005-08-31
- 修回日期: 2006-02-24
- 刊出日期: 2007-04-19

A New Algorithm of Ship Targets Detection in SAR Images Using Wavelet Transform

Chen De-yuan^{①②;凃国防},
Tu Guo-fang

摘要

摘要: 根据小波变换和Teager能量算子(TEO)的局部特性，该文提出一种基于SAR图像的船舰检测算法。该算法对SAR图像进行小波变换，计算小波系数的Teager能量。根据小波域的Teager能量对船舰信号的增强特性，使用双参数CFAR检测SAR图像船舰。仿真结果表明，新算法与传统的双参数CFAR检测算法和基于K-分布的单元平均检测算法相比，在船舰检测数和虚警数性能指标上均优于传统检测算法。
- 合成孔径雷达;小波变换;船舰检测;Teager能量算子
Abstract: Using the local nature of wavelet transform and Teager energy operator (TEO), a novel scheme is proposed to detect ship targets in SAR images based on TEO wavelet enhancement. The algorithm applies wavelet transform to SAR image and computes the Teager energy of every wavelet coefficient of the high frequency components. According to the property of the Teager energy which enhances the ship signals of SAR image, two-parameter Constant False Alarm Rate(CFAR) detection algorithm is applied to the enhanced SAR image to detect ship targets. The simulating results show that the new detector improves detection performance comparing with the two-parameter CFAR detector and the cell average detection based on K-distribution.

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