ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 451-455, 2017
https://doi.org/10.5194/isprs-annals-IV-2-W4-451-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
14 Sep 2017
G0-WISHART DISTRIBUTION BASED CLASSIFICATION FROM POLARIMETRIC SAR IMAGES
G. C. Hu and Q. H. Zhao Institute for Remote Sencing Science and Application, School of Geomatics, Liaoning Technical University, Fuxin, Liaoning,123000, China
Keywords: G0-Wishart distribution, Classification, Polarimetric SAR Images, G0-Wishart distance, H/A/α decomposition Abstract. Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.
Conference paper (PDF, 2652 KB)


Citation: Hu, G. C. and Zhao, Q. H.: G0-WISHART DISTRIBUTION BASED CLASSIFICATION FROM POLARIMETRIC SAR IMAGES, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 451-455, https://doi.org/10.5194/isprs-annals-IV-2-W4-451-2017, 2017.

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