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Classification Method for Fully PolSAR Data Based on Three Novel Parameters
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DOI：10.1109/LGRS.2013.2245628.png)
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In this letter, a new classification method for fully polarimetric synthetic aperture radar (PolSAR) data based on three novel parameters is presented. The three parameters are derived from the eigenspace of the coherency matrix as linear combinations of its three eigenvalues. In the proposed classification method, the maximum value out of the three parameters is determined to assign a label to each image pixel, and the PolSAR image is classified into three classes accordingly. Experimental results based on NASA/JPL AIRSAR L-band data and CSA RADARSAT-2 C-band data illustrate the validity and efficacy of the procedure.
Keyword:
Image classification
radar polarimetry
scattering mechanism
target decomposition
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16.4
论文数:
1.0W
被引数:
5.1K
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Unsupervised classification of polarimetric synthetic aperture radar images using fuzzy clustering and EM clustering基于模糊聚类和EM聚类的极化合成孔径雷达图像无监督分类
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