Polarimetric synthetic aperture radar (PolSAR) plays an important role in the field of building extraction because of its multi-parameter, multi-channel, multi-polarization, and rich information records. Taking Radarsat-2 image of Suzhou in 2017 as an example,19 polarization features and 8 texture features are extracted by polarization non-coherent decomposition methods and GLCM, respectively. Based on the analysis of features, we obtain the results of building extraction by PCA feature fusion and SVM algorithm. The results show that the extraction accuracies based on polarization features and texture feature are 92.4% and 88.9%, respectively. The accuracy is 93.7% when the polarization and texture features are used together. The combination of polarization and texture features improves the accuracy and the PCA feature fusion increases both efficiency and precision.
MA Xiaoxiao
,
CHENG Bo
,
LIU Yueming
,
CUI Shiai
,
LIANG Chenbin
. PolSAR remote sensing image method for building extraction based on polarization and texture characteristics[J]. Journal of University of Chinese Academy of Sciences, 2019
, 36(5)
: 682
-693
.
DOI: 10.7523/j.issn.2095-6134.2019.05.014
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