Acta Geodaetica et Cartographica Sinica

   

Mixed Pixels Classification of Remote Sensing Images Based on Support Vector Machines and Pairwise Coupling

Hui li, Yunpeng Wang, Yan li, Xingfang Wang   

  • Received:1900-01-01 Revised:1900-01-01 Online:2011-12-28 Published:2019-01-01

Abstract: Support Vector Machines (SVM) with pairwise coupling (PWC) method is designed to estimate abundance fractions of materials in remote sensing image. PWC method maps the SVM outputs into posteriori probabilities which are regarded as abundances of each material. Multi-channel remote sensing images data are used to validate the method. The experiment result shows that the method can provide better result of abundance estimation as compared with general linear-model and it can get good result in image classification.