A statistical 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...
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| Veröffentlicht in: | Frontiers of information technology & electronic engineering 2017-10, Vol.18 (10), p.1614-1623 |
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| container_title | Frontiers of information technology & electronic engineering |
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| creator | He, Chu Ye, Ya-ping Tian, Ling Yang, Guo-peng Chen, Dong |
| description | 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 statistics. Experimental results on Terra SAR data demonstrate the effectiveness of the proposed s-texton feature. |
| doi_str_mv | 10.1631/FITEE.1601051 |
| format | Article |
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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 statistics. 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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 statistics. 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| subjects | Classification Clustering Communications Engineering Computer Hardware Computer Science Computer Systems Organization and Communication Networks Data analysis Electrical Engineering Electronics and Microelectronics Engineering Fourier transforms Heuristic Image classification Instrumentation Labeling Networks Parameter estimation Probability distribution R&D Radar imaging Random variables Remote sensing Research & development Statistics Synthetic aperture radar Texture |
| title | A statistical distribution texton feature for synthetic aperture radar image classification |
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