| CLASSIFICATION OF MULTI-LOOK POLARIMETRIC SAR IMAGERY AND POLARIZATION CHANNEL OPTIMIZATION |
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| 基金项目： | This work was performed at Alenia Spazio,Rome,Italy.It was a part of the cooperation project between Alenia Spazio and University of Electronic Science and Technology of China,Chengdu,China |
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| 摘 要： | In this paper, a new maximum likelihood (ML) classification algorithm is proposed to classify the multi-look polarimetric synthetic aperture radar (SAR) imagery. Experimental results with the NASA/JPL airborne L-band polarimetric SAR data demonstrate the effectiveness of the new algorithm. Furthermore, when using the algorithm in the classifications with subsets of the multi-look polarimetric SAR data, the polarization-channel optimization for the terrain type classification is implemented.
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Classification of multi-look polarimetric SAR imagery and polarization channel optimization |
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| Authors: | Guoqing Liu Hong Xiong Shunji Huang A Torre F Rubertone |
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| Affiliation: | (1) College of Electron. Eng., Univ. of Electron. Sci. & Tech. of China, 610054 Chengdu;(2) Dept. of Remote Sensing, Alenia Spazio SPA, 00131 Rome, Italy |
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| Abstract: | In this paper, a new maximum likelihood (ML) classification algorithm is proposed to classify the multi-look polarimetric synthetic aperture radar (SAR) imagery. Experimental results with the NASA/JPL airborne L-band polarimetric SAR data demonstrate the effectiveness of the new algorithm. Furthermore, when using the algorithm in the classifications with subsets of the multi-look polarimetric SAR data, the polarization-channel optimization for the terrain type classification is implemented. |
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| Keywords: | Polarimetric SAR Multi-look processing Speckle Classification Polarization-channel optimization |
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