{"title":"Application Research of Support Vector Machine in Multi-Spectra Remote Sensing Image Classification","authors":"Yujian Wang, Jiazheng Yuan, Lili Fan, Zhiguo Liu","doi":"10.1109/CISP.2009.5305618","DOIUrl":null,"url":null,"abstract":"In order to improve the accuracy of multi-spectra remote sensing image classification, a terrain classification method based on support vector machine is proposed. A remote sensing image classification method based on SVM algorithm of C-SVC type is introduced and emphasis is put on the study of the improved SMO algorithm. In order to improve efficiency of classification, multiple-spectra remote sensing image classification of terrain is classified using fuzzy clustering based on fuzzy c-means algorithm which adopt semi-supervised improved algorithm. The experimental results show that the approach has an advantage over traditional classification methods.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"337 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5305618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In order to improve the accuracy of multi-spectra remote sensing image classification, a terrain classification method based on support vector machine is proposed. A remote sensing image classification method based on SVM algorithm of C-SVC type is introduced and emphasis is put on the study of the improved SMO algorithm. In order to improve efficiency of classification, multiple-spectra remote sensing image classification of terrain is classified using fuzzy clustering based on fuzzy c-means algorithm which adopt semi-supervised improved algorithm. The experimental results show that the approach has an advantage over traditional classification methods.