全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于D-S证据理论的多特征融合SAR图像目标识别方法

DOI: 10.6046/gtzyyg.2013.02.07, PP. 37-41

Keywords: SAR图像,D-S证据理论,支持向量机(SVM),纹理特征

Full-Text   Cite this paper   Add to My Lib

Abstract:

针对应用单特征SAR图像进行目标识别准确率低的问题,提出了一种将支持向量机(supportvectormachine,SVM)和D-S证据理论(Dempster-Shafer,D-S)相结合的多特征融合SAR图像目标识别方法。该方法在对SAR图像预处理的基础上,提取目标的纹理、Hu不变矩和峰值特征,并分别以这3类单特征的SVM分类结果作为独立证据,构造基本概率指派,通过D-S证据的组合规则进行融合,并根据分类判决门限给出最终的目标识别结果。将该方法用于SAR图像上的3类目标识别,识别率达95.5%,表明该方法是一种有效的SAR图像目标识别方法。

References

[1]  刘爱平,付琨,张利利,等.基于多尺度特征的高分辨率SAR图像机动目标识别[J].系统工程与电子技术,2010,32(6):1163-1165. Liu A P,Fu K,Zhang L L,et al.Maneuvering target recognition of high resolution SAR images based on multi-scale feature[J].Systems Engineering and Electronics,2010,32(6):1163-1165.
[2]  张静,王国宏,梁发麦,等.基于证据理论的SAR图像融合识别方法[J].系统仿真学报,2007,19(9):2053-2056. Zhang J,Wang G H,Liang F M,et al.Study on fusion recognition method of target’s SAR images based on D-S evidence theory[J].Journal of System Simulation,2007,19(9):2053-2056.
[3]  Zhao Q,Principe J C.Support vector machines for SAR automatic target recognition[J].IEEE Trans on Aerospace and Electronic Systems,2001,37(2):643-654.
[4]  Vapnic V N.Statistical learning theory[M].New York:Wiley,1998.
[5]  傅文杰,洪金益,朱谷昌.基于SVM遥感矿化蚀变信息提取研究[J].国土资源遥感,2006,18(2):17-19. Fu W J,Hong J Y,Zhu G C.The extraction of mineralized and altered rock information from remote sensing image based on SVM[J].Remote Sensing for Land and Resources,2006,18(2):17-19.
[6]  Yager R R.On the dempster shafer framework and new combination rules[J].Information System,1989,41(2):93-137.
[7]  郝颖明,朱枫.2维Otsu自适应阈值的快速算法[J].中国图象图形学报,2005,10(4):484-488. Hao Y M,Zhu F.Fast algorithm for two-dimensional Ostu adaptive threshold algorithm[J].Journal of Image and Graphics,2005,10(4):484-488.
[8]  Hu M K.Visual pattern recognition by moment invariants[J].IEEE Trans on Information Theory,1962,12(6):170-179.
[9]  Platt J C.Probabilistic output for support vector machine and comparisons to regularized likelihood methods[G]//Smola A J.Advances in Large Margin Classifiers,Cambridge,MA:MIT Press,1999:1-11.
[10]  付燕,詹新光.一种有效的SAR图像目标识别方法[J].计算机工程与应用,2010,46(15):156-157. Fu Y,Zhan X G.Efficient method of SAR image target recognition[J].Computer Engineering and Application,2010,46(15):156-157.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133