Research on target classification for SAR images based on C-Means and support vector machines

Author

Lihai, Yuan ; Jianshe, Song ; Jialong, Ge ; Kai, Jiang

Author_Institution

Dept. of Radar Imaging, East China Res. Inst. of Electron. Eng., Hefei, China

fYear

2009

fDate

25-27 May 2009

Firstpage

1592

Lastpage

1596

Abstract

Aim at multiplicative speckle noise and little difference among targets in synthetic aperture radar (SAR) images, a target classification algorithm is proposed based on C-Means and support vector machines (SVMs). Its front part adopts a C-Means clustering method to classify targets and suppress speckle noise in feature space, and its back part adopts an SVM classifier to improve classification accuracy in image space. Experimental results show that this algorithm can reduce the dimension of SVM and have a better classification performance using Ku-band SAR database.

Keywords

image classification; image resolution; pattern clustering; radar computing; radar imaging; support vector machines; synthetic aperture radar; SAR image target classification; c-means clustering method; high-resolution SAR image; multiplicative speckle noise; support vector machine; synthetic aperture radar; Classification algorithms; Clustering algorithms; Clustering methods; Image classification; Radar imaging; Speckle; Support vector machine classification; Support vector machines; Synthetic aperture radar; Target recognition; image processing; support vector machine; synthetic aperture radar (SAR) image; target classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4244-2799-4

Electronic_ISBN

978-1-4244-2800-7

Type

conf

DOI

10.1109/ICIEA.2009.5138463

Filename

5138463