Remote sensing image classification based on SVM and object semantic

Abstract

Multispectral remote sensing images have been regarded as dataset which contains incredible semantic information. And classifying multispectral remote sensing images could, in a sense, be achieved by analyzing a variety of complex semantic information and distilling skeletonzed information which facilitates the generalization, calculation and decision-making of human beings. However, conventional interpretation of remote sensing images is mostly limited within the extent of feature extraction and selection of merely spectral features of terrestrial objects. This paper present a Remote sensing Image Classification method based on SVM and Object Semantic, and it can obtain better performance of image classification. © Springer-Verlag Berlin Heidelberg 2013.