{"title":"Statistical modelling of Polarization Fraction for classification of PolSAR images using GMM","authors":"Ayush Chauhan, H. Maurya, R. K. Panigrahi","doi":"10.1109/APMC.2016.7931377","DOIUrl":null,"url":null,"abstract":"This paper presents a statistical model to classify the PolSAR image on the basis of Polarization Fraction (PF) of the backscattered wave. The basic principle behind PF, i.e., the relative power in the co-polarized and cross-polarized channel, is employed to distinguish between surface, double-bounce and volume scattering. We look to find the best fit model to the measured data by assuming it to be Gaussian distributed. A Radarsat-2 image of San Francisco is used to illustrate the results.","PeriodicalId":166478,"journal":{"name":"2016 Asia-Pacific Microwave Conference (APMC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Asia-Pacific Microwave Conference (APMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APMC.2016.7931377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a statistical model to classify the PolSAR image on the basis of Polarization Fraction (PF) of the backscattered wave. The basic principle behind PF, i.e., the relative power in the co-polarized and cross-polarized channel, is employed to distinguish between surface, double-bounce and volume scattering. We look to find the best fit model to the measured data by assuming it to be Gaussian distributed. A Radarsat-2 image of San Francisco is used to illustrate the results.
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