Astatistical distribution texton feature for synthetic aperture radar image classification
Chu HE, Ya-ping YE, Ling TIAN, Guo-peng YANG, Dong CHEN
Astatistical distribution texton feature for synthetic aperture radar image classification
We propose a novel statistical distribution texton (s-texton) feature for synthetic aperture radar (SAR) image classification. Motivated by the traditional texton feature, the framework of texture analysis, and the importance of statistical distribution in SAR images, the s-texton feature is developed based on the idea that parameter estimation of the statistical distribution can replace the filtering operation in the traditional texture analysis of SAR images. In the process of extracting the s-texton feature, several strategies are adopted, including pre-processing, spatial gridding, parameter estimation, texton clustering, and histogram
Synthetic aperture radar / Statistical distribution / Parameter estimation / Image classification
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