采用独立分量分析Zernike矩的遥感图像飞机目标识别

PDF下载HTML

Title:

Research concerning aircraft recognition of remote sensing images based on ICA Zernike invariant moments

文章编号:

1673-4785(2011)01-0051-06

作者:

刘富����^1,2��，于鹏��¹，刘坤��¹

1.吉林大学 通信工程学院，吉林 长春 130022；
2.哈尔滨工业大学 深空探测基础研究中心，黑龙江 哈尔滨 150001

Author(s):

LIU Fu����^1,2��, YU Peng��¹, LIU Kun^��1

1.College of Communications Engineering, Jilin University, Changchun 130022, China;
2.Deep Space Exploration Research Center, Harbin Institute of Technology, Harbin 150001, China

关键词:

独立分量分析; Zernike矩; 遥感图像; 飞机目标识别

Keywords:

independent component algorithm (ICA);  Zernike invariant moments;  remote sensing images;  aircraft target recognition

分类号:

TP391.41

文献标志码:

A

摘要:

为了提高遥感图像目标自动识别系统的准确性，提出了一种新的采用独立分量分析（ICA) Zernike矩的飞机目标识别方法.首先对分割后的目标区域进行独立分量分析处理，将待识别目标形状转换到标准形式，然后对标准化后的图像目标提取Zernike矩作为特征向量进行识别.通过实验表明此方法具有鲁棒性，能有效地消除遥感图像目标尺度、旋转、平移、反转和扭曲影响，能够有效地识别遥感图像飞机目标.

Abstract:

To promote the accuracy of an automatic target recognition (ATR) system for remote sensing images, a novel feature recognition method was proposed for an airplane target based on the independent component algorithm (ICA) with Zernike invariant moments. First, the divided region of interest (ROI) was analyzed with the ICA method. Also, the shape of the target was changed to canonical form. Then, the invariant moments of normalized shapes could be extracted. They would potentially be used as a feature vector to do further recognition. The experiment demonstrates that the performance of this method is robust. It can eliminate the effects of scaling, rotation, translation, reflection, and skewing of the remote sensing image target. Furthermore, this method can recognize an airplane’s target from the remote sensing images effectively.