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