Title :
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
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;
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
DOI :
10.1109/ICIEA.2009.5138463