DocumentCode :
1607234
Title :
Application of AdaBoost in polarimetric SAR image classification
Author :
Min, Rui ; Yang, Xiaobo ; Zhao, Zhiqin
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
fYear :
2009
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, a method of polarimetric SAR image classification based on polarimetric decomposition and AdaBoost algorithm is proposed. The proposed method improves classification accuracy and speed. AdaBoost algorithm, as a robust learner with high accuracy, can fully utilize the polarimetric features to achieve image classification. In simulated tests, the proposed method is observed to produce improved classification accuracy and speed, compared with H /alphamacr classification algorithm.
Keywords :
feature extraction; image classification; learning (artificial intelligence); radar imaging; radar polarimetry; synthetic aperture radar; AdaBoost algorithm; polarimetric SAR image classification; robust learner; synthetic aperture radar; Boosting; Classification algorithms; Eigenvalues and eigenfunctions; Image classification; Matrix decomposition; Polarization; Robustness; Scattering; Synthetic aperture radar; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Conference, 2009 IEEE
Conference_Location :
Pasadena, CA
ISSN :
1097-5659
Print_ISBN :
978-1-4244-2870-0
Electronic_ISBN :
1097-5659
Type :
conf
DOI :
10.1109/RADAR.2009.4976988
Filename :
4976988
Link To Document :
بازگشت