期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：7
页码：17-26
DOI：10.14257/ijsip.2015.8.7.03
出版社：SERSC
摘要：Through the research of the application of support vector machine theory in the pixel unmixing, the advantages of the weighted posterior probability support vector machine theory in pixel unmixing is presented. Considering the difference of each support vector machine classifier, posterior probability pixel is used as weight coefficient of sub-pixel classification for pixels unmixing. This paper presents a weighted posterior probability support vector machine mixed pixel unmixing method. This method not only has the nonlinear model decomposition characteristics of high precision, but also reduces the standard support vector machine calculating the amount of multi classifier, and it has strong adaptability
关键词：pixel unmixing; end-member extraction; data field; weighted posterior ; probability support vector machine
