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Integrating color features in polarimetric SAR image classification |
| BU Lijing1, HUANG Pengyan2, SHEN Lu1 |
1. School of Mapping and Geographical Science, Liaoning Technical University, Fuxin 123000, China;
2. School of Civil Engineering, Luoyang Institute of Science and Technology, Luoyang 471000, China |
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Abstract This paper presents a method for combining the color feature and target decomposition characteristics so as to study the classification of polarimetric SAR. It makes up decomposition feature vector by polarimetric target decomposition and then, through the pseudo color enhancement method, obtains the false color image of polarimetric SAR data representation; after that, it extracts color histogram from the pseudo color images to make up the color feature vector, thus providing additional information for further land classification. Classification experiments were performed at different feature vectors by using RadarSat-2 polarimetric SAR image. In addition, the quantitative and qualitative comparison analysis was conducted with classification results. The experimental results show that the addition of the color feature can effectively improve the classification accuracy of polarimetric SAR images.
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| Keywords
snow cover fraction(SCF)
spatio-temporal distribution
MODIS
DEM
Tibetan Plateau
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Issue Date: 15 August 2017
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2017,
Vol. 29
