Title :
Application Research of Support Vector Machine in Multi-Spectra Remote Sensing Image Classification
Author :
Wang, Yujian ; Yuan, Jiazheng ; Fan, Lili ; Liu, Zhiguo
Author_Institution :
Inst. of Inf. Technol., Beijing Union Univ., Beijing, China
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.
Keywords :
fuzzy set theory; geophysical signal processing; image classification; learning (artificial intelligence); pattern clustering; support vector machines; terrain mapping; SVM algorithm; fuzzy c-means algorithm; fuzzy clustering; improved SMO algorithm; multispectra remote sensing image classification; semisupervised improved algorithm; support vector machine; terrain classification method; Clustering algorithms; Image classification; Information technology; Pattern recognition; Remote sensing; Risk management; Satellites; Space technology; Support vector machine classification; Support vector machines;
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
DOI :
10.1109/CISP.2009.5305618